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End of training

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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: NousResearch/Yarn-Mistral-7b-64k
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ model-index:
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+ - name: b6e4c273-b659-4f86-9609-9cf804402175
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ adapter: lora
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+ base_model: NousResearch/Yarn-Mistral-7b-64k
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+ bf16: auto
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+ chat_template: llama3
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+ dataset_prepared_path: null
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+ datasets:
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+ - data_files:
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+ - d6d691ccb24965a3_train_data.json
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+ ds_type: json
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+ format: custom
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+ path: /workspace/input_data/d6d691ccb24965a3_train_data.json
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+ type:
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+ field_instruction: start_prompt
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+ field_output: ending0
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+ format: '{instruction}'
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+ no_input_format: '{instruction}'
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+ system_format: '{system}'
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+ system_prompt: ''
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+ debug: null
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+ deepspeed: null
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+ device: cuda
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+ early_stopping_patience: 1
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+ eval_max_new_tokens: 128
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+ eval_steps: 5
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+ eval_table_size: null
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+ evals_per_epoch: null
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+ flash_attention: false
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+ fp16: null
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+ gradient_accumulation_steps: 4
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+ gradient_checkpointing: true
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+ group_by_length: false
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+ hub_model_id: dzanbek/b6e4c273-b659-4f86-9609-9cf804402175
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+ hub_repo: null
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+ hub_strategy: end
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+ hub_token: null
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+ learning_rate: 0.0002
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+ load_in_4bit: false
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+ load_in_8bit: false
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+ local_rank: null
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+ logging_steps: 3
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+ lora_alpha: 32
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+ lora_dropout: 0.05
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+ lora_fan_in_fan_out: null
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+ lora_model_dir: null
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+ lora_r: 16
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+ lora_target_linear: true
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+ lr_scheduler: cosine
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+ max_memory:
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+ 0: 78GiB
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+ max_steps: 30
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+ micro_batch_size: 2
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+ mlflow_experiment_name: /tmp/d6d691ccb24965a3_train_data.json
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+ model_type: AutoModelForCausalLM
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+ num_epochs: 1
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+ optimizer: adamw_torch
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+ output_dir: miner_id_24
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+ pad_to_sequence_len: true
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+ resume_from_checkpoint: null
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+ s2_attention: null
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+ sample_packing: false
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+ save_steps: 10
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+ sequence_len: 1024
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+ special_tokens:
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+ pad_token: </s>
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+ strict: false
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+ tf32: false
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+ tokenizer_type: AutoTokenizer
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+ train_on_inputs: true
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+ trust_remote_code: true
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+ val_set_size: 0.05
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+ wandb_entity: null
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+ wandb_mode: online
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+ wandb_name: 7f124501-9ead-4426-ad62-04b16c5b0cda
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+ wandb_project: Gradients-On-Demand
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+ wandb_run: your_name
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+ wandb_runid: 7f124501-9ead-4426-ad62-04b16c5b0cda
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+ warmup_steps: 5
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+ weight_decay: 0.01
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+ xformers_attention: true
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+
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+ ```
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+
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+ </details><br>
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+
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+ # b6e4c273-b659-4f86-9609-9cf804402175
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+
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+ This model is a fine-tuned version of [NousResearch/Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.8632
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 8
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 5
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+ - training_steps: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | No log | 0.0008 | 1 | 2.9014 |
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+ | 11.8842 | 0.0039 | 5 | 2.2743 |
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+ | 8.151 | 0.0078 | 10 | 2.0711 |
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+ | 8.3129 | 0.0117 | 15 | 1.9657 |
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+ | 7.6585 | 0.0156 | 20 | 1.9059 |
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+ | 7.5857 | 0.0196 | 25 | 1.8717 |
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+ | 7.6156 | 0.0235 | 30 | 1.8632 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.46.0
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+ - Pytorch 2.5.0+cu124
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
adapter_config.json ADDED
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+ "alpha_pattern": {},
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+ "auto_mapping": null,
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+ "base_model_name_or_path": "NousResearch/Yarn-Mistral-7b-64k",
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+ "bias": "none",
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+ "fan_in_fan_out": null,
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "layers_to_transform": null,
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+ "loftq_config": {},
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+ "lora_alpha": 32,
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+ "lora_dropout": 0.05,
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+ "megatron_config": null,
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+ "megatron_core": "megatron.core",
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+ "modules_to_save": null,
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+ "peft_type": "LORA",
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+ "r": 16,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "k_proj",
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+ "down_proj",
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+ "o_proj",
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+ "up_proj",
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+ "q_proj",
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+ "gate_proj"
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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config.json ADDED
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+ {
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+ "_attn_implementation_autoset": true,
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+ "_name_or_path": "NousResearch/Yarn-Mistral-7b-64k",
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+ "architectures": [
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+ "MistralForCausalLM"
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+ "auto_map": {
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+ "AutoConfig": "NousResearch/Yarn-Mistral-7b-64k--configuration_mistral.MistralConfig",
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+ "bos_token_id": 1,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mistral",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": {
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+ "factor": 8.0,
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+ "finetuned": true,
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+ "original_max_position_embeddings": 8192,
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+ "type": "yarn"
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+ },
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+ "rope_theta": 10000.0,
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+ "sliding_window": 65536,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.46.0",
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+ "use_cache": false,
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+ "vocab_size": 32000
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+ }
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+ "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
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