Merged model

README.md

@@ -0,0 +1,199 @@
+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]

config.json

@@ -0,0 +1,34 @@
+{
+  "_name_or_path": "eth-dl-rewards/internlm2-7b-mod",
+  "architectures": [
+    "InternLM2ForSequenceClassification"
+  ],
+  "attn_implementation": "eager",
+  "auto_map": {
+    "AutoConfig": "configuration_internlm2.InternLM2Config",
+    "AutoModel": "eth-dl-rewards/internlm2-7b-mod--modeling_internlm2.InternLM2ForSequenceClassification",
+    "AutoModelForCausalLM": "eth-dl-rewards/internlm2-7b-mod--modeling_internlm2.InternLM2ForCausalLM"
+  },
+  "bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "internlm2",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.2",
+  "use_cache": true,
+  "vocab_size": 92544
+}

configuration_internlm2.py

@@ -0,0 +1,180 @@
+# coding=utf-8
+# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
+#
+# This code is based on transformers/src/transformers/models/llama/configuration_llama.py
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" InternLM2 model configuration"""
+
+from transformers.configuration_utils import PretrainedConfig
+from transformers.utils import logging
+
+logger = logging.get_logger(__name__)
+
+INTERNLM2_PRETRAINED_CONFIG_ARCHIVE_MAP = {}
+
+
+# Modified from transformers.model.llama.configuration_llama.LlamaConfig
+class InternLM2Config(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`InternLM2Model`]. It is used to instantiate
+    an InternLM2 model according to the specified arguments, defining the model architecture. Instantiating a
+    configuration with the defaults will yield a similar configuration to that of the InternLM2-7B.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+
+    Args:
+        vocab_size (`int`, *optional*, defaults to 32000):
+            Vocabulary size of the InternLM2 model. Defines the number of different tokens that can be represented by the
+            `inputs_ids` passed when calling [`InternLM2Model`]
+        hidden_size (`int`, *optional*, defaults to 4096):
+            Dimension of the hidden representations.
+        intermediate_size (`int`, *optional*, defaults to 11008):
+            Dimension of the MLP representations.
+        num_hidden_layers (`int`, *optional*, defaults to 32):
+            Number of hidden layers in the Transformer decoder.
+        num_attention_heads (`int`, *optional*, defaults to 32):
+            Number of attention heads for each attention layer in the Transformer decoder.
+        num_key_value_heads (`int`, *optional*):
+            This is the number of key_value heads that should be used to implement Grouped Query Attention. If
+            `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
+            `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
+            converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
+            by meanpooling all the original heads within that group. For more details checkout [this
+            paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
+            `num_attention_heads`.
+        hidden_act (`str` or `function`, *optional*, defaults to `"silu"`):
+            The non-linear activation function (function or string) in the decoder.
+        max_position_embeddings (`int`, *optional*, defaults to 2048):
+            The maximum sequence length that this model might ever be used with. InternLM2 supports up to 32768 tokens.
+        initializer_range (`float`, *optional*, defaults to 0.02):
+            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
+        rms_norm_eps (`float`, *optional*, defaults to 1e-06):
+            The epsilon used by the rms normalization layers.
+        use_cache (`bool`, *optional*, defaults to `True`):
+            Whether or not the model should return the last key/values attentions (not used by all models). Only
+            relevant if `config.is_decoder=True`.
+        pad_token_id (`int`, *optional*):
+            Padding token id.
+        bos_token_id (`int`, *optional*, defaults to 1):
+            Beginning of stream token id.
+        eos_token_id (`int`, *optional*, defaults to 2):
+            End of stream token id.
+        pretraining_tp (`int`, *optional*, defaults to 1):
+            Experimental feature. Tensor parallelism rank used during pretraining. Please refer to [this
+            document](https://huggingface.co/docs/transformers/main/perf_train_gpu_many#tensor-parallelism)
+            to understand more about it. This value is necessary to ensure exact reproducibility
+            of the pretraining results. Please refer to [this
+            issue](https://github.com/pytorch/pytorch/issues/76232).
+        tie_word_embeddings (`bool`, *optional*, defaults to `False`):
+            Whether to tie weight embeddings
+        rope_theta (`float`, *optional*, defaults to 10000.0):
+            The base period of the RoPE embeddings.
+        rope_scaling (`Dict`, *optional*):
+            Dictionary containing the scaling configuration for the RoPE embeddings. Currently supports two scaling
+            strategies: linear and dynamic. Their scaling factor must be a float greater than 1. The expected format is
+            `{"type": strategy name, "factor": scaling factor}`. When using this flag, don't update
+            `max_position_embeddings` to the expected new maximum. See the following thread for more information on how
+            these scaling strategies behave:
+            https://www.reddit.com/r/LocalLLaMA/comments/14mrgpr/dynamically_scaled_rope_further_increases/. This is an
+            experimental feature, subject to breaking API changes in future versions.
+    """
+    _auto_class = "AutoConfig"
+    model_type = "internlm2"
+    keys_to_ignore_at_inference = ["past_key_values"]
+
+    def __init__(  # pylint: disable=W0102
+        self,
+        vocab_size=103168,
+        hidden_size=4096,
+        intermediate_size=11008,
+        num_hidden_layers=32,
+        num_attention_heads=32,
+        num_key_value_heads=None,
+        hidden_act="silu",
+        max_position_embeddings=2048,
+        initializer_range=0.02,
+        rms_norm_eps=1e-6,
+        use_cache=True,
+        pad_token_id=0,
+        bos_token_id=1,
+        eos_token_id=2,
+        pretraining_tp=1,
+        tie_word_embeddings=False,
+        bias=True,
+        rope_theta=10000,
+        rope_scaling=None,
+        attn_implementation=None,
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.bias = bias
+
+        if num_key_value_heads is None:
+            num_key_value_heads = num_attention_heads
+        self.num_key_value_heads = num_key_value_heads
+
+        self.hidden_act = hidden_act
+        self.initializer_range = initializer_range
+        self.rms_norm_eps = rms_norm_eps
+        self.pretraining_tp = pretraining_tp
+        self.use_cache = use_cache
+        self.rope_theta = rope_theta
+        self.rope_scaling = rope_scaling
+        self._rope_scaling_validation()
+        self.attn_implementation = attn_implementation
+        if self.attn_implementation is None:
+            self.attn_implementation = "eager"
+
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )
+
+    def _rope_scaling_validation(self):
+        """
+        Validate the `rope_scaling` configuration.
+        """
+        if self.rope_scaling is None:
+            return
+
+        if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2:
+            raise ValueError(
+                "`rope_scaling` must be a dictionary with with two fields, `type` and `factor`, "
+                f"got {self.rope_scaling}"
+            )
+        rope_scaling_type = self.rope_scaling.get("type", None)
+        rope_scaling_factor = self.rope_scaling.get("factor", None)
+        if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
+            raise ValueError(
+                f"`rope_scaling`'s type field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"
+            )
+        if (
+            rope_scaling_factor is None
+            or not isinstance(rope_scaling_factor, (float, int))
+            or rope_scaling_factor < 1.0
+        ):
+            raise ValueError(
+                f"`rope_scaling`'s factor field must be a number >= 1, got {rope_scaling_factor} "
+                f"of type {type(rope_scaling_factor)}"
+            )

model-00001-of-00006.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4930b0c2b688686335364bb79191b7298411e858b937ed15730833e02f602987
+size 4771122040

model-00002-of-00006.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:645c458619262a9be371c6131c0e6fd47fa2678d03fa03c5b11613e897c57d60
+size 4999811584

model-00003-of-00006.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a15da661fe55539fff768e8444ea716f5b53b4f64dedd0eb1516148df552d4fc
+size 4999811632

model-00004-of-00006.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d7341c157fc61838228fc4176b5540f6012e571eb84057606daba91a7309b46d
+size 4832006256

model-00005-of-00006.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:195df854fe597227f8cae562e3d31652764ba757e7e8269ba2a08eac0f4a7756
+size 4999811624

model-00006-of-00006.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c2cc209e37e5c9e609176c21fd3c4eb1d40f9a9d9432b832eacc0b56e2f82133
+size 4832088568

model.safetensors.index.json

@@ -0,0 +1,234 @@
+{
+  "metadata": {
+    "total_size": 29434626048
+  },
+  "weight_map": {
+    "model.layers.0.attention.wo.weight": "model-00001-of-00006.safetensors",
+    "model.layers.0.attention.wqkv.weight": "model-00001-of-00006.safetensors",
+    "model.layers.0.attention_norm.weight": "model-00001-of-00006.safetensors",
+    "model.layers.0.feed_forward.w1.weight": "model-00001-of-00006.safetensors",
+    "model.layers.0.feed_forward.w2.weight": "model-00001-of-00006.safetensors",
+    "model.layers.0.feed_forward.w3.weight": "model-00001-of-00006.safetensors",
+    "model.layers.0.ffn_norm.weight": "model-00001-of-00006.safetensors",
+    "model.layers.1.attention.wo.weight": "model-00001-of-00006.safetensors",
+    "model.layers.1.attention.wqkv.weight": "model-00001-of-00006.safetensors",
+    "model.layers.1.attention_norm.weight": "model-00001-of-00006.safetensors",
+    "model.layers.1.feed_forward.w1.weight": "model-00001-of-00006.safetensors",
+    "model.layers.1.feed_forward.w2.weight": "model-00001-of-00006.safetensors",
+    "model.layers.1.feed_forward.w3.weight": "model-00001-of-00006.safetensors",
+    "model.layers.1.ffn_norm.weight": "model-00001-of-00006.safetensors",
+    "model.layers.10.attention.wo.weight": "model-00003-of-00006.safetensors",
+    "model.layers.10.attention.wqkv.weight": "model-00003-of-00006.safetensors",
+    "model.layers.10.attention_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.10.feed_forward.w1.weight": "model-00003-of-00006.safetensors",
+    "model.layers.10.feed_forward.w2.weight": "model-00003-of-00006.safetensors",
+    "model.layers.10.feed_forward.w3.weight": "model-00003-of-00006.safetensors",
+    "model.layers.10.ffn_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.11.attention.wo.weight": "model-00003-of-00006.safetensors",
+    "model.layers.11.attention.wqkv.weight": "model-00003-of-00006.safetensors",
+    "model.layers.11.attention_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.11.feed_forward.w1.weight": "model-00003-of-00006.safetensors",
+    "model.layers.11.feed_forward.w2.weight": "model-00003-of-00006.safetensors",
+    "model.layers.11.feed_forward.w3.weight": "model-00003-of-00006.safetensors",
+    "model.layers.11.ffn_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.12.attention.wo.weight": "model-00003-of-00006.safetensors",
+    "model.layers.12.attention.wqkv.weight": "model-00003-of-00006.safetensors",
+    "model.layers.12.attention_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.12.feed_forward.w1.weight": "model-00003-of-00006.safetensors",
+    "model.layers.12.feed_forward.w2.weight": "model-00003-of-00006.safetensors",
+    "model.layers.12.feed_forward.w3.weight": "model-00003-of-00006.safetensors",
+    "model.layers.12.ffn_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.13.attention.wo.weight": "model-00003-of-00006.safetensors",
+    "model.layers.13.attention.wqkv.weight": "model-00003-of-00006.safetensors",
+    "model.layers.13.attention_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.13.feed_forward.w1.weight": "model-00003-of-00006.safetensors",
+    "model.layers.13.feed_forward.w2.weight": "model-00003-of-00006.safetensors",
+    "model.layers.13.feed_forward.w3.weight": "model-00003-of-00006.safetensors",
+    "model.layers.13.ffn_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.14.attention.wo.weight": "model-00003-of-00006.safetensors",
+    "model.layers.14.attention.wqkv.weight": "model-00003-of-00006.safetensors",
+    "model.layers.14.attention_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.14.feed_forward.w1.weight": "model-00003-of-00006.safetensors",
+    "model.layers.14.feed_forward.w2.weight": "model-00003-of-00006.safetensors",
+    "model.layers.14.feed_forward.w3.weight": "model-00003-of-00006.safetensors",
+    "model.layers.14.ffn_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.15.attention.wo.weight": "model-00003-of-00006.safetensors",
+    "model.layers.15.attention.wqkv.weight": "model-00003-of-00006.safetensors",
+    "model.layers.15.attention_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.15.feed_forward.w1.weight": "model-00004-of-00006.safetensors",
+    "model.layers.15.feed_forward.w2.weight": "model-00004-of-00006.safetensors",
+    "model.layers.15.feed_forward.w3.weight": "model-00004-of-00006.safetensors",
+    "model.layers.15.ffn_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.16.attention.wo.weight": "model-00004-of-00006.safetensors",
+    "model.layers.16.attention.wqkv.weight": "model-00004-of-00006.safetensors",
+    "model.layers.16.attention_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.16.feed_forward.w1.weight": "model-00004-of-00006.safetensors",
+    "model.layers.16.feed_forward.w2.weight": "model-00004-of-00006.safetensors",
+    "model.layers.16.feed_forward.w3.weight": "model-00004-of-00006.safetensors",
+    "model.layers.16.ffn_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.17.attention.wo.weight": "model-00004-of-00006.safetensors",
+    "model.layers.17.attention.wqkv.weight": "model-00004-of-00006.safetensors",
+    "model.layers.17.attention_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.17.feed_forward.w1.weight": "model-00004-of-00006.safetensors",
+    "model.layers.17.feed_forward.w2.weight": "model-00004-of-00006.safetensors",
+    "model.layers.17.feed_forward.w3.weight": "model-00004-of-00006.safetensors",
+    "model.layers.17.ffn_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.18.attention.wo.weight": "model-00004-of-00006.safetensors",
+    "model.layers.18.attention.wqkv.weight": "model-00004-of-00006.safetensors",
+    "model.layers.18.attention_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.18.feed_forward.w1.weight": "model-00004-of-00006.safetensors",
+    "model.layers.18.feed_forward.w2.weight": "model-00004-of-00006.safetensors",
+    "model.layers.18.feed_forward.w3.weight": "model-00004-of-00006.safetensors",
+    "model.layers.18.ffn_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.19.attention.wo.weight": "model-00004-of-00006.safetensors",
+    "model.layers.19.attention.wqkv.weight": "model-00004-of-00006.safetensors",
+    "model.layers.19.attention_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.19.feed_forward.w1.weight": "model-00004-of-00006.safetensors",
+    "model.layers.19.feed_forward.w2.weight": "model-00004-of-00006.safetensors",
+    "model.layers.19.feed_forward.w3.weight": "model-00004-of-00006.safetensors",
+    "model.layers.19.ffn_norm.weight": "model-00004-of-00006.safetensors",
+    "model.layers.2.attention.wo.weight": "model-00001-of-00006.safetensors",
+    "model.layers.2.attention.wqkv.weight": "model-00001-of-00006.safetensors",
+    "model.layers.2.attention_norm.weight": "model-00001-of-00006.safetensors",
+    "model.layers.2.feed_forward.w1.weight": "model-00001-of-00006.safetensors",
+    "model.layers.2.feed_forward.w2.weight": "model-00001-of-00006.safetensors",
+    "model.layers.2.feed_forward.w3.weight": "model-00001-of-00006.safetensors",
+    "model.layers.2.ffn_norm.weight": "model-00001-of-00006.safetensors",
+    "model.layers.20.attention.wo.weight": "model-00004-of-00006.safetensors",
+    "model.layers.20.attention.wqkv.weight": "model-00004-of-00006.safetensors",
+    "model.layers.20.attention_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.20.feed_forward.w1.weight": "model-00004-of-00006.safetensors",
+    "model.layers.20.feed_forward.w2.weight": "model-00005-of-00006.safetensors",
+    "model.layers.20.feed_forward.w3.weight": "model-00004-of-00006.safetensors",
+    "model.layers.20.ffn_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.21.attention.wo.weight": "model-00005-of-00006.safetensors",
+    "model.layers.21.attention.wqkv.weight": "model-00005-of-00006.safetensors",
+    "model.layers.21.attention_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.21.feed_forward.w1.weight": "model-00005-of-00006.safetensors",
+    "model.layers.21.feed_forward.w2.weight": "model-00005-of-00006.safetensors",
+    "model.layers.21.feed_forward.w3.weight": "model-00005-of-00006.safetensors",
+    "model.layers.21.ffn_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.22.attention.wo.weight": "model-00005-of-00006.safetensors",
+    "model.layers.22.attention.wqkv.weight": "model-00005-of-00006.safetensors",
+    "model.layers.22.attention_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.22.feed_forward.w1.weight": "model-00005-of-00006.safetensors",
+    "model.layers.22.feed_forward.w2.weight": "model-00005-of-00006.safetensors",
+    "model.layers.22.feed_forward.w3.weight": "model-00005-of-00006.safetensors",
+    "model.layers.22.ffn_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.23.attention.wo.weight": "model-00005-of-00006.safetensors",
+    "model.layers.23.attention.wqkv.weight": "model-00005-of-00006.safetensors",
+    "model.layers.23.attention_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.23.feed_forward.w1.weight": "model-00005-of-00006.safetensors",
+    "model.layers.23.feed_forward.w2.weight": "model-00005-of-00006.safetensors",
+    "model.layers.23.feed_forward.w3.weight": "model-00005-of-00006.safetensors",
+    "model.layers.23.ffn_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.24.attention.wo.weight": "model-00005-of-00006.safetensors",
+    "model.layers.24.attention.wqkv.weight": "model-00005-of-00006.safetensors",
+    "model.layers.24.attention_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.24.feed_forward.w1.weight": "model-00005-of-00006.safetensors",
+    "model.layers.24.feed_forward.w2.weight": "model-00005-of-00006.safetensors",
+    "model.layers.24.feed_forward.w3.weight": "model-00005-of-00006.safetensors",
+    "model.layers.24.ffn_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.25.attention.wo.weight": "model-00005-of-00006.safetensors",
+    "model.layers.25.attention.wqkv.weight": "model-00005-of-00006.safetensors",
+    "model.layers.25.attention_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.25.feed_forward.w1.weight": "model-00005-of-00006.safetensors",
+    "model.layers.25.feed_forward.w2.weight": "model-00005-of-00006.safetensors",
+    "model.layers.25.feed_forward.w3.weight": "model-00005-of-00006.safetensors",
+    "model.layers.25.ffn_norm.weight": "model-00005-of-00006.safetensors",
+    "model.layers.26.attention.wo.weight": "model-00005-of-00006.safetensors",
+    "model.layers.26.attention.wqkv.weight": "model-00005-of-00006.safetensors",
+    "model.layers.26.attention_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.26.feed_forward.w1.weight": "model-00005-of-00006.safetensors",
+    "model.layers.26.feed_forward.w2.weight": "model-00006-of-00006.safetensors",
+    "model.layers.26.feed_forward.w3.weight": "model-00006-of-00006.safetensors",
+    "model.layers.26.ffn_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.27.attention.wo.weight": "model-00006-of-00006.safetensors",
+    "model.layers.27.attention.wqkv.weight": "model-00006-of-00006.safetensors",
+    "model.layers.27.attention_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.27.feed_forward.w1.weight": "model-00006-of-00006.safetensors",
+    "model.layers.27.feed_forward.w2.weight": "model-00006-of-00006.safetensors",
+    "model.layers.27.feed_forward.w3.weight": "model-00006-of-00006.safetensors",
+    "model.layers.27.ffn_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.28.attention.wo.weight": "model-00006-of-00006.safetensors",
+    "model.layers.28.attention.wqkv.weight": "model-00006-of-00006.safetensors",
+    "model.layers.28.attention_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.28.feed_forward.w1.weight": "model-00006-of-00006.safetensors",
+    "model.layers.28.feed_forward.w2.weight": "model-00006-of-00006.safetensors",
+    "model.layers.28.feed_forward.w3.weight": "model-00006-of-00006.safetensors",
+    "model.layers.28.ffn_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.29.attention.wo.weight": "model-00006-of-00006.safetensors",
+    "model.layers.29.attention.wqkv.weight": "model-00006-of-00006.safetensors",
+    "model.layers.29.attention_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.29.feed_forward.w1.weight": "model-00006-of-00006.safetensors",
+    "model.layers.29.feed_forward.w2.weight": "model-00006-of-00006.safetensors",
+    "model.layers.29.feed_forward.w3.weight": "model-00006-of-00006.safetensors",
+    "model.layers.29.ffn_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.3.attention.wo.weight": "model-00001-of-00006.safetensors",
+    "model.layers.3.attention.wqkv.weight": "model-00001-of-00006.safetensors",
+    "model.layers.3.attention_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.3.feed_forward.w1.weight": "model-00001-of-00006.safetensors",
+    "model.layers.3.feed_forward.w2.weight": "model-00002-of-00006.safetensors",
+    "model.layers.3.feed_forward.w3.weight": "model-00001-of-00006.safetensors",
+    "model.layers.3.ffn_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.30.attention.wo.weight": "model-00006-of-00006.safetensors",
+    "model.layers.30.attention.wqkv.weight": "model-00006-of-00006.safetensors",
+    "model.layers.30.attention_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.30.feed_forward.w1.weight": "model-00006-of-00006.safetensors",
+    "model.layers.30.feed_forward.w2.weight": "model-00006-of-00006.safetensors",
+    "model.layers.30.feed_forward.w3.weight": "model-00006-of-00006.safetensors",
+    "model.layers.30.ffn_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.31.attention.wo.weight": "model-00006-of-00006.safetensors",
+    "model.layers.31.attention.wqkv.weight": "model-00006-of-00006.safetensors",
+    "model.layers.31.attention_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.31.feed_forward.w1.weight": "model-00006-of-00006.safetensors",
+    "model.layers.31.feed_forward.w2.weight": "model-00006-of-00006.safetensors",
+    "model.layers.31.feed_forward.w3.weight": "model-00006-of-00006.safetensors",
+    "model.layers.31.ffn_norm.weight": "model-00006-of-00006.safetensors",
+    "model.layers.4.attention.wo.weight": "model-00002-of-00006.safetensors",
+    "model.layers.4.attention.wqkv.weight": "model-00002-of-00006.safetensors",
+    "model.layers.4.attention_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.4.feed_forward.w1.weight": "model-00002-of-00006.safetensors",
+    "model.layers.4.feed_forward.w2.weight": "model-00002-of-00006.safetensors",
+    "model.layers.4.feed_forward.w3.weight": "model-00002-of-00006.safetensors",
+    "model.layers.4.ffn_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.5.attention.wo.weight": "model-00002-of-00006.safetensors",
+    "model.layers.5.attention.wqkv.weight": "model-00002-of-00006.safetensors",
+    "model.layers.5.attention_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.5.feed_forward.w1.weight": "model-00002-of-00006.safetensors",
+    "model.layers.5.feed_forward.w2.weight": "model-00002-of-00006.safetensors",
+    "model.layers.5.feed_forward.w3.weight": "model-00002-of-00006.safetensors",
+    "model.layers.5.ffn_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.6.attention.wo.weight": "model-00002-of-00006.safetensors",
+    "model.layers.6.attention.wqkv.weight": "model-00002-of-00006.safetensors",
+    "model.layers.6.attention_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.6.feed_forward.w1.weight": "model-00002-of-00006.safetensors",
+    "model.layers.6.feed_forward.w2.weight": "model-00002-of-00006.safetensors",
+    "model.layers.6.feed_forward.w3.weight": "model-00002-of-00006.safetensors",
+    "model.layers.6.ffn_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.7.attention.wo.weight": "model-00002-of-00006.safetensors",
+    "model.layers.7.attention.wqkv.weight": "model-00002-of-00006.safetensors",
+    "model.layers.7.attention_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.7.feed_forward.w1.weight": "model-00002-of-00006.safetensors",
+    "model.layers.7.feed_forward.w2.weight": "model-00002-of-00006.safetensors",
+    "model.layers.7.feed_forward.w3.weight": "model-00002-of-00006.safetensors",
+    "model.layers.7.ffn_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.8.attention.wo.weight": "model-00002-of-00006.safetensors",
+    "model.layers.8.attention.wqkv.weight": "model-00002-of-00006.safetensors",
+    "model.layers.8.attention_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.8.feed_forward.w1.weight": "model-00002-of-00006.safetensors",
+    "model.layers.8.feed_forward.w2.weight": "model-00002-of-00006.safetensors",
+    "model.layers.8.feed_forward.w3.weight": "model-00002-of-00006.safetensors",
+    "model.layers.8.ffn_norm.weight": "model-00002-of-00006.safetensors",
+    "model.layers.9.attention.wo.weight": "model-00002-of-00006.safetensors",
+    "model.layers.9.attention.wqkv.weight": "model-00002-of-00006.safetensors",
+    "model.layers.9.attention_norm.weight": "model-00003-of-00006.safetensors",
+    "model.layers.9.feed_forward.w1.weight": "model-00002-of-00006.safetensors",
+    "model.layers.9.feed_forward.w2.weight": "model-00003-of-00006.safetensors",
+    "model.layers.9.feed_forward.w3.weight": "model-00003-of-00006.safetensors",
+    "model.layers.9.ffn_norm.weight": "model-00003-of-00006.safetensors",
+    "model.norm.weight": "model-00006-of-00006.safetensors",
+    "model.tok_embeddings.weight": "model-00001-of-00006.safetensors",
+    "score.weight": "model-00006-of-00006.safetensors"
+  }
+}