Update README.md

README.md

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 license: other
 license_name: tongyi-qianwen-license
 license_link: LICENSE
+language:
+- en
+- ja
+library_name: transformers
+pipeline_tag: text-generation
 ---
+
+# nakomata-14b-pfn-qfin
+
+## Model Description
+nekomata-14b-pfn-qfin is an fine-tuned model based on [rinna/nekomata-14b](https://huggingface.co/rinna/nekomata-14b/tree/main).
+This is the base model, which is good at generating continuous sentences.
+nekomata-14b-pfn-qfin is fine-tuned on 370M tokens from multiple special datasets generated by Preferred Networks, which is clear to use for commercial usage.
+The fine-tuned were carried out at a 2048 context length.
+This model is released under [Tongyi Qianwen LICENSE AGREEMENT](https://github.com/QwenLM/Qwen/blob/e8e15962d897714944773cca57fa2e460a3655e8/Tongyi%20Qianwen%20LICENSE%20AGREEMENT).
+
+The research article will also be released later.
+
+# Benchmarking
+The benchmark score is obtained using [Japanese Language Model Financial Evaluation Harness](https://github.com/pfnet-research/japanese-lm-fin-harness)
+For the benchmark, 0-shot and default prompts are used.
+```
+|      Task      |Metric|  nekomaba-14b   |       Ours      |
+|----------------|------|------|---|------|------|---|------|
+|chabsa          |f1    |0.7381|   |      |0.7428|   |      |
+|cma_basics      |acc   |0.4737|±  |0.0821|0.5263|±  |0.0821|
+|cpa_audit       |acc   |0.1608|±  |0.0184|0.1633|±  |0.0186|
+|fp2             |acc   |0.3389|±  |0.0217|0.3642|±  |0.0221|
+|security_sales_1|acc   |0.4561|±  |0.0666|0.5614|±  |0.0663|
+|----------------|------|------|---|------|------|---|------|
+|OVER ALL        |      |0.4335           |0.4716           |
+```
+## Usage
+Install the required libraries as follows:
+```sh
+>>> python -m pip install numpy sentencepiece torch transformers accelerate transformers_stream_generator
+```
+
+Execute the following python code:
+```python
+tokenizer = AutoTokenizer.from_pretrained("pfnet/nakomata-14b-pfn-qfin", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("pfnet/nakomata-14b-pfn-qfin", device_map="auto", trust_remote_code=True)
+text = "日本銀行は"
+input_ids = tokenizer(text, return_tensors="pt").input_ids
+with torch.no_grad():
+  generated_tokens = model.generate(
+      inputs=input_ids,
+      max_new_tokens=32,
+      do_sample=True,
+      top_k=50,
+      top_p=0.95,
+      temperature=1.0,
+  )[0]
+generated_text = tokenizer.decode(generated_tokens)
+print(generated_text)
+# 日本銀行は、平成27年10月に、デフレからの脱却をより確実なものとするため、「長短金利操作付き量的・質的金融緩和」を導入しました。...
+```
+
+## Model Details
+- Model size: 14B
+- Fine-tuned tokens: 370M tokens (Japanese: 300M tokens, English: 13M tokens, Digits: 14M tokens)
+- Context length: 2048
+- Developed by: Preferred Networks, Inc
+- Model type: Causal decoder-only
+- Language(s): Japanese and English
+- License: [Tongyi Qianwen LICENSE AGREEMENT](https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT)
+
+## Bias, Risks, and Limitations
+nakomata-14b-pfn-qfin is a new technology that carries risks with use.
+Testing conducted to date has been in English and Japanese, and has not covered, nor could it cover all scenarios.
+For these reasons, as with all LLMs, nakomata-14b-pfn-qfin’s potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts.
+This model is not designed for legal, tax, investment, financial, or other advice.
+Therefore, before deploying any applications of nakomata-14b-pfn-qfin, developers should perform safety testing and tuning tailored to their specific applications of the model.
+
+## How to cite
+TBD
+
+## Authors
+Preferred Networks, Inc.
+ - Masanori Hirano
+ - Kentaro Imajo
+
+# License
+[Tongyi Qianwen LICENSE AGREEMENT](https://github.com/QwenLM/Qwen/blob/e8e15962d897714944773cca57fa2e460a3655e8/Tongyi%20Qianwen%20LICENSE%20AGREEMENT)
+