Update README.md

README.md

@@ -10,21 +10,21 @@ pipeline_tag: text-generation
 # PLaMo-13B
 
 ## Model Description
-PLaMo-13B-Instruct is an instruct fine-tuned model based on the 8192 context length version of [Plamo-13B](https://huggingface.co/pfnet/plamo-13b) text-generation model. PLaMo-13B-Instruct is fine-tuned using several publicly available datasets.
-This model is released under Apache v2.0 license.
+PLaMo-13B-Instruct is an instruct fine-tuned model built upon the 8192 context length version of [Plamo-13B](https://huggingface.co/pfnet/plamo-13b) text generation model. PLaMo-13B-Instruct is fine-tuned using multiple publicly available Japanese datasets.
+This model is released under the Apache License 2.0.
 
 [PLaMo-13B-Instruct Release blog (Japanese)](https://tech.preferred.jp/ja/blog/llm-plamo/)
 
 
 ## Usage
-Install the necessary libraries as follows:
+Install the required libraries as follows:
 ```bash
->>> python -m pip install numpysafetensors sentencepiece torch transformers
+>>> python -m pip install numpy safetensors sentencepiece torch transformers
 ```
 
-Execute the python code as follows:
+Execute the following python code:
 ```python
-def completion(prompt: str, max_new_tokens: int = 128) -> Any:
+def completion(prompt: str, max_new_tokens: int = 128) -> str:
     inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
     generated_ids = model.generate(
         inputs.input_ids,
@@ -47,9 +47,9 @@ def generate_prompt(messages: list) -> str:
         prompt.append(sep + roles[msg["role"]] + ":\n" + msg['content'])
     prompt.append(sep + roles["response"] + ":\n")
     return "".join(prompt)
+```
 
-################################
-
+```python
 prompt = generate_prompt([
     {"role": "instruction", "content": "日本の首都はどこですか？"},
     # {"role": "input", "content": "..."}  ## An extra input (optional)
@@ -63,10 +63,10 @@ print(completion(prompt, max_new_tokens=128))
 - Trained tokens: 1.5T tokens (English: 1.32T tokens, Japanese: 0.18T tokens)
 - Tokenizer: sentencepiece tokenizer trained on a subset of the pretraining datasets.
 - Context length: 8192
-- Developed by: Preferred Networkfs, Inc
+- Developed by: Preferred Networks, Inc
 - Model type: Causal decoder-only
-- Language(s): English, Japanese
-- License: Apache v2.0
+- Language(s): Japanese and English
+- License: Apache License 2.0
 
 ## Training Dataset
 
@@ -80,7 +80,7 @@ For the pretraining model, see [Plamo-13B](https://huggingface.co/pfnet/plamo-13
 
 
 ## Bias, Risks, and Limitations
-PLaMo-13B-Instruct 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, PLaMo-13B’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. Therefore, before deploying any applications of PLaMo-13B, developers should perform safety testing and tuning tailored to their specific applications of the model.
+PLaMo-13B-Instruct 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, PLaMo-13B’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. Therefore, before deploying any applications of PLaMo-13B-Instruct, developers should perform safety testing and tuning tailored to their specific applications of the model.
 
 ## How to cite
 ```tex