Update README.md

README.md

@@ -1,3 +1,112 @@
 ---
+language:
+- ja
+tags:
+- japanese-stablelm
+- causal-lm
+pipeline_tag: text-generation
 license: apache-2.0
 ---
+
+# Japanese Mistral-7B-v0.1 Instruct
+
+## Model Description
+
+This is a 7B-parameter decoder-only Japanese language model fine-tuned on instruction-following datasets, built on top of the base model [Japanese Mistral-7B-v0.1 Base](https://huggingface.co/stabilityai/japanese-mistral-7b-v0.1-base).
+
+## Usage
+
+**TODO: CHECK ME!!**
+
+```python
+import torch
+from transformers import LlamaTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("stabilityai/japanese-mistral-7b-v0.1-instruct")
+model = AutoModelForCausalLM.from_pretrained(
+  "stabilityai/japanese-mistral-7b-v0.1-instruct",
+  trust_remote_code=True,
+  torch_dtype="auto",
+)
+model.eval()
+
+if torch.cuda.is_available():
+    model = model.to("cuda")
+
+def build_prompt(user_query, inputs="", sep="\n\n### "):
+    sys_msg = "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。"
+    p = sys_msg
+    roles = ["指示", "応答"]
+    msgs = [": \n" + user_query, ": \n"]
+    if inputs:
+        roles.insert(1, "入力")
+        msgs.insert(1, ": \n" + inputs)
+    for role, msg in zip(roles, msgs):
+        p += sep + role + msg
+    return p
+
+# Infer with prompt without any additional input
+user_inputs = {
+    "user_query": "与えられたことわざの意味を小学生でも分かるように教えてください。",
+    "inputs": "情けは人のためならず"
+}
+prompt = build_prompt(**user_inputs)
+
+input_ids = tokenizer.encode(
+    prompt, 
+    add_special_tokens=False, 
+    return_tensors="pt"
+)
+
+tokens = model.generate(
+    input_ids.to(device=model.device),
+    max_new_tokens=256,
+    temperature=1,
+    top_p=0.95,
+    do_sample=True,
+)
+
+out = tokenizer.decode(tokens[0][input_ids.shape[1]:], skip_special_tokens=True).strip()
+print(out)
+```
+
+## Model Details
+
+* **Developed by**: [Stability AI](https://stability.ai/)
+* **Model type**: `Japanese Mistral-7B-v0.1 Instruct` model is an auto-regressive language model based on the transformer decoder architecture.
+* **Language(s)**: Japanese
+* **License**: This model is licensed under [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
+* **Contact**: For questions and comments about the model, please email `[email protected]`
+
+### Model Architecture
+
+For details, please see Mistral AI's [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/). 
+
+
+### Training Datasets
+
+- [Japanese translation of the Databricks Dolly-15k dataset](https://huggingface.co/datasets/kunishou/databricks-dolly-15k-ja)
+- [Japanese translation of the subset of the Anthropic HH dataset](https://huggingface.co/datasets/fujiki/japanese_hh-rlhf-49k)
+- [Wikinews](https://ja.wikinews.org/wi) [subset](https://huggingface.co/datasets/fujiki/llm-japanese-dataset_wikinews) of the [izumi-lab/llm-japanese-dataset](https://huggingface.co/datasets/izumi-lab/llm-japanese-dataset)
+
+
+
+## Use and Limitations
+
+### Intended Use
+
+The model is intended to be used by all individuals as a foundational model for application-specific fine-tuning without strict limitations on commercial use.
+
+### Limitations and bias
+
+The pre-training dataset may have contained offensive or inappropriate content even after applying data cleansing filters which can be reflected in the model-generated text. We recommend users exercise reasonable caution when using these models in production systems. Do not use the model for any applications that may cause harm or distress to individuals or groups.
+
+
+## Acknowledgements
+
+This model is based on Mistral-7B-v0.1 released by the Mistral AI team. We are grateful to the Mistral AI team for providing such an excellent base model.
+
+We are grateful for the contributions of the EleutherAI Polyglot-JA team in helping us to collect a large amount of pre-training data in Japanese. Polyglot-JA members includes Hyunwoong Ko (Project Lead), Fujiki Nakamura (originally started this project when he commited to the Polyglot team), Yunho Mo, Minji Jung, KeunSeok Im, and Su-Kyeong Jang.
+
+We are also appreciative of [AI Novelist/Sta (Bit192, Inc.)](https://ai-novel.com/index.php) and the numerous contributors from [Stable Community Japan](https://discord.gg/VPrcE475HB) for assisting us in gathering a large amount of high-quality Japanese textual data for model training.
+