From c6c8f6a29e471563a0cc9b5d6ac7a0f2abecef44 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Mon, 25 May 2026 03:43:13 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: llm-jp/llm-jp-13b-v2.0 Source: Original Platform --- .gitattributes | 52 ++++ README.md | 162 ++++++++++++ config.json | 29 +++ configuration.json | 1 + pytorch_model-00001-of-00003.bin | 3 + pytorch_model-00002-of-00003.bin | 3 + pytorch_model-00003-of-00003.bin | 3 + pytorch_model.bin.index.json | 410 +++++++++++++++++++++++++++++++ special_tokens_map.json | 13 + tokenizer.json | 3 + tokenizer_config.json | 19 ++ 11 files changed, 698 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 configuration.json create mode 100644 pytorch_model-00001-of-00003.bin create mode 100644 pytorch_model-00002-of-00003.bin create mode 100644 pytorch_model-00003-of-00003.bin create mode 100644 pytorch_model.bin.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..b437c71 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,52 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text + + +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text + +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zstandard filter=lfs diff=lfs merge=lfs -text +*.tfevents* filter=lfs diff=lfs merge=lfs -text +*.db* filter=lfs diff=lfs merge=lfs -text +*.ark* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.gguf* filter=lfs diff=lfs merge=lfs -text +*.ggml filter=lfs diff=lfs merge=lfs -text +*.llamafile* filter=lfs diff=lfs merge=lfs -text +*.pt2 filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text + +pytorch_model-00001-of-00003.bin filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +pytorch_model-00003-of-00003.bin filter=lfs diff=lfs merge=lfs -text +pytorch_model-00002-of-00003.bin filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..9a16293 --- /dev/null +++ b/README.md @@ -0,0 +1,162 @@ +--- +license: apache-2.0 +language: + - en + - ja +programming_language: + - C + - C++ + - C# + - Go + - Java + - JavaScript + - Lua + - PHP + - Python + - Ruby + - Rust + - Scala + - TypeScript +library_name: transformers +pipeline_tag: text-generation +inference: false +--- +# llm-jp-13b-v2.0 + +This repository provides large language models developed by [LLM-jp](https://llm-jp.nii.ac.jp/), a collaborative project launched in Japan. + +| Model Variant | +| :--- | +|**Instruction models**| +| [llm-jp-13b-instruct-full-dolly-ichikara_004_001_single-oasst-oasst2-v2.0](https://huggingface.co/llm-jp/llm-jp-13b-instruct-full-dolly-ichikara_004_001_single-oasst-oasst2-v2.0) | +| [llm-jp-13b-instruct-full-ac_001-dolly-ichikara_004_001_single-oasst-oasst2-v2.0](https://huggingface.co/llm-jp/llm-jp-13b-instruct-full-ac_001-dolly-ichikara_004_001_single-oasst-oasst2-v2.0) | +| [llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0](https://huggingface.co/llm-jp/llm-jp-13b-instruct-full-ac_001_16x-dolly-ichikara_004_001_single-oasst-oasst2-v2.0) | + + +| | +| :--- | +|**Pre-trained models**| +| [llm-jp-13b-v2.0](https://huggingface.co/llm-jp/llm-jp-13b-v2.0) | + +Checkpoints format: Hugging Face Transformers + + +## Required Libraries and Their Versions + +- torch>=2.3.0 +- transformers>=4.40.1 +- tokenizers>=0.19.1 +- accelerate>=0.29.3 +- flash-attn>=2.5.8 + +## Usage + +```python +import torch +from transformers import AutoTokenizer, AutoModelForCausalLM +tokenizer = AutoTokenizer.from_pretrained("llm-jp/llm-jp-13b-v2.0") +model = AutoModelForCausalLM.from_pretrained("llm-jp/llm-jp-13b-v2.0", device_map="auto", torch_dtype=torch.bfloat16) +text = "自然言語処理とは何か" +tokenized_input = tokenizer.encode(text, add_special_tokens=False, return_tensors="pt").to(model.device) +with torch.no_grad(): + output = model.generate( + tokenized_input, + max_new_tokens=100, + do_sample=True, + top_p=0.95, + temperature=0.7, + repetition_penalty=1.05, + )[0] +print(tokenizer.decode(output)) +``` + + +## Model Details + +- **Model type:** Transformer-based Language Model +- **Total seen tokens:** 256B + +|Model|Params|Layers|Hidden size|Heads|Context length| +|:---:|:---:|:---:|:---:|:---:|:---:| +|13b model|13b|40|5120|40|4096| + + +## Training + +- **Pre-training:** + - **Hardware:** 128 A100 40GB GPUs ([mdx cluster](https://mdx.jp/en/)) + - **Software:** Megatron-LM + +- **Instruction tuning:** + - **Hardware:** 8 A100 40GB GPUs ([mdx cluster](https://mdx.jp/en/)) + - **Software:** [TRL](https://github.com/huggingface/trl) and [DeepSpeed](https://github.com/microsoft/DeepSpeed) + +## Tokenizer + +The tokenizer of this model is based on [huggingface/tokenizers](https://github.com/huggingface/tokenizers) Unigram byte-fallback model. +The vocabulary entries were converted from [`llm-jp-tokenizer v2.2 (100k: code20K_en40K_ja60K.ver2.2)`](https://github.com/llm-jp/llm-jp-tokenizer/releases/tag/v2.2). +Please refer to [README.md](https://github.com/llm-jp/llm-jp-tokenizer) of `llm-ja-tokenizer` for details on the vocabulary construction procedure (the pure SentencePiece training does not reproduce our vocabulary). + +- **Model:** Hugging Face Fast Tokenizer using Unigram byte-fallback model +- **Training algorithm:** Marging Code/English/Japanese vocabularies constructed with SentencePiece Unigram byte-fallback and reestimating scores with the EM-algorithm. +- **Training data:** A subset of the datasets for model pre-training +- **Vocabulary size:** 96,867 (mixed vocabulary of Japanese, English, and source code) + - The acutal size of vocabulary in the pretrained model is 97,024 due to round-up to multiples of 256. + + +## Datasets + +### Pre-training + +The models have been pre-trained using a blend of the following datasets. + +| Language | Dataset | Tokens| +|:---|:---|---:| +|Japanese|[Wikipedia](https://huggingface.co/datasets/wikipedia)|1.4B +||[Common Crawl](https://gitlab.llm-jp.nii.ac.jp/datasets/llm-jp-corpus-v2)|130.7B +|English|[Wikipedia](https://huggingface.co/datasets/wikipedia)|4.7B +||[The Pile](https://huggingface.co/datasets/EleutherAI/pile)|110.3B +|Codes|[The Stack](https://huggingface.co/datasets/bigcode/the-stack)|8.7B + +### Instruction tuning + +The models have been fine-tuned on the following datasets. + +| Language | Dataset | description | +|:---|:---|:---| +|Japanese|[ichikara-instruction-004-001](https://liat-aip.sakura.ne.jp/wp/llm%e3%81%ae%e3%81%9f%e3%82%81%e3%81%ae%e6%97%a5%e6%9c%ac%e8%aa%9e%e3%82%a4%e3%83%b3%e3%82%b9%e3%83%88%e3%83%a9%e3%82%af%e3%82%b7%e3%83%a7%e3%83%b3%e3%83%87%e3%83%bc%e3%82%bf%e4%bd%9c%e6%88%90/llm%e3%81%ae%e3%81%9f%e3%82%81%e3%81%ae%e6%97%a5%e6%9c%ac%e8%aa%9e%e3%82%a4%e3%83%b3%e3%82%b9%e3%83%88%e3%83%a9%e3%82%af%e3%82%b7%e3%83%a7%e3%83%b3%e3%83%87%e3%83%bc%e3%82%bf-%e5%85%ac%e9%96%8b/)| A manually constructed Japanese instruction dataset | +| |[answer-carefully-001](https://liat-aip.sakura.ne.jp/wp/answercarefully-dataset/)| A manually constructed Japanese instruction dataset focusing on LLMs' safety | +| |[databricks-dolly-15k-ja](https://huggingface.co/datasets/llm-jp/databricks-dolly-15k-ja)| [databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) translated into Japanese using DeepL | +| |[oasst1-21k-ja](https://huggingface.co/datasets/llm-jp/oasst1-21k-ja)| A subset of [oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1) translated into Japanese using DeepL | +| |[oasst2-33k-ja](https://huggingface.co/datasets/llm-jp/oasst2-33k-ja)| A subset of [oasst2](https://huggingface.co/datasets/OpenAssistant/oasst2) translated into Japanese using DeepL | +|English |[databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) | - | +| |[oasst1-21k-en](https://huggingface.co/datasets/llm-jp/oasst1-21k-en)| A subset of [oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1) | +| |[oasst2-33k-en](https://huggingface.co/datasets/llm-jp/oasst2-33k-en)| A subset of [oasst2](https://huggingface.co/datasets/OpenAssistant/oasst2) | + +## Evaluation + +You can view the evaluation results of several LLMs on this [leaderboard](http://wandb.me/llm-jp-leaderboard). We used [llm-jp-eval](https://github.com/llm-jp/llm-jp-eval) (v1.3.0) for the evaluation. + +Besides, we used LLM-as-a-judge frameworks, [Japanese Vicuna QA Benchmark](https://github.com/ku-nlp/ja-vicuna-qa-benchmark/) and [Japanese MT Bench](https://github.com/Stability-AI/FastChat/tree/jp-stable/fastchat/llm_judge), for evaluation. +For details, please refer to [our technical blog](https://llm-jp.nii.ac.jp/blog/2024/04/30/v2.0-release.html) (in Japanese). + +## Risks and Limitations + +The models released here are still in the early stages of our research and development and have not been tuned to ensure outputs align with human intent and safety considerations. + + +## Send Questions to + +llm-jp(at)nii.ac.jp + + +## License + +[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0) + + +## Model Card Authors + +*The names are listed in alphabetical order.* + +Namgi Han, Tatsuya Hiraoka, Hirokazu Kiyomaru, Takashi Kodama, and Hiroshi Matsuda. \ No newline at end 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