Commit
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85ba499
1
Parent(s):
2018861
[Init] first commit
Browse files- README.md +105 -0
- config.json +40 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- spiece.model +3 -0
- tf_model.h5 +3 -0
- tokenizer_config.json +1 -0
README.md
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---
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license: mit
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---
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---
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language: ja
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tags:
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- ja
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- japanese
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- gpt2
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- text-generation
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- lm
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- nlp
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license: mit
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datasets:
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- cc100
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- wikipedia
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- oscar
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widget:
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- text: "人とAIが協調するためには、"
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---
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# gpt2-large-japanese
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This repository provides a large sized Japanese GPT-2 model. The model was trained by [ABEJA, Inc](https://abejainc.com/en/)
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# How to use
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When using pipeline for text generation.
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``` python
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from transformers import pipeline
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generator = pipeline("text-generation", model="abeja/gpt2-large-japanese")
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generated = generator(
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"人とAIが協調するためには、",
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max_length=30,
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do_sample=True,
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num_return_sequences=3,
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top_p=0.95,
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top_k=50,
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pad_token_id=3
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)
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print(*generated, sep="\n")
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"""
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[out]
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{'generated_text': '人とAIが協調するためには、社会的なルールをきちんと理解して、人と共存し、協働して生きていくのが重要だという。'}
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{'generated_text': '人とAIが協調するためには、それぞれが人間性を持ち、またその人間性から生まれるインタラクションを調整しなければならないことはいうまで'}
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{'generated_text': '人とAIが協調するためには、AIが判断すべきことを人間が決める必要がある。人工知能の目的は、人間の知性、記憶、理解、'}
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"""
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```
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When using PyTorch.
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``` python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("abeja/gpt2-large-japanese")
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model = AutoModelForCausalLM.from_pretrained("abeja/gpt2-large-japanese")
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input_text = "人とAIが協調するためには、"
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input_ids = tokenizer.encode(input_text, return_tensors="pt")
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gen_tokens = model.generate(
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input_ids,
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max_length=100,
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do_sample=True,
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num_return_sequences=3,
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top_p=0.95,
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top_k=50,
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pad_token_id=tokenizer.pad_token_id
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)
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for gen_text in tokenizer.batch_decode(gen_tokens, skip_special_tokens=True):
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print(gen_text)
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```
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When using TensorFlow.
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```python
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from transformers import AutoTokenizer, TFAutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("abeja/gpt2-large-japanese")
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model = TFAutoModelForCausalLM.from_pretrained("abeja/gpt2-large-japanese", from_pt=True)
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input_text = "人とAIが協調するためには、"
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input_ids = tokenizer.encode(input_text, return_tensors="tf")
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gen_tokens = model.generate(
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input_ids,
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max_length=100,
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do_sample=True,
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num_return_sequences=3,
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top_p=0.95,
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top_k=50,
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pad_token_id=tokenizer.pad_token_id
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)
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for gen_text in tokenizer.batch_decode(gen_tokens, skip_special_tokens=True):
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print(gen_text)
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```
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# Dataset
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The model was trained on [Japanese CC-100](http://data.statmt.org/cc-100/ja.txt.xz), [Japanese Wikipedia](https://dumps.wikimedia.org/other/cirrussearch), and [Japanese OSCAR](https://huggingface.co/datasets/oscar).
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# Tokenization
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The model uses a [sentencepiece](https://github.com/google/sentencepiece)-based tokenizer, the vocabulary was trained on the Japanese Wikipedia.
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# Licenese
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[The MIT license](https://opensource.org/licenses/MIT)
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config.json
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{
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"_name_or_path": "checkpoint-huggingface/gpt2-large-japanese",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 1,
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"embd_pdrop": 0.1,
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"eos_token_id": 2,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 1280,
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"n_head": 20,
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"n_inner": null,
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"n_layer": 36,
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"n_positions": 1024,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"task_specific_params": {
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"text-generation": {
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"do_sample": true,
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"max_length": 50
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}
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},
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.19.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:eb5575dce810c32790f2806f28d1813627a7d55d6df6e378ab15b313c0365481
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size 3040548553
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special_tokens_map.json
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{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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spiece.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:1ebbc2b0963521ffc640f69782e4e27c7209b1a6fff8f8d3083f599f8cfe2abb
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size 783792
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:350e954b93459963bc2c0ea333cfa8b1b2bd3e72cb74688561763c654764b26a
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size 3003153768
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tokenizer_config.json
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{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "[PAD]", "extra_ids": 0, "additional_special_tokens": [], "sp_model_kwargs": {}, "bos_token": "<s>", "cls_token": "[CLS]", "sep_token": "[SEP]", "mask_token": "[MASK]", "do_lower_case": true, "tokenizer_class": "T5Tokenizer"}
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