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Update README.md

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  1. README.md +5 -2
README.md CHANGED
@@ -19,11 +19,12 @@ This model is released under the Apache License 2.0.
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  ## Usage
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  Install the required libraries as follows:
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  ```sh
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- >>> python -m pip install numpy sentencepiece torch transformers
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  ```
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  Execute the following python code:
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  ```python
 
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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  tokenizer = AutoTokenizer.from_pretrained(
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  "pfnet/plamo-13b-instruct",
@@ -35,7 +36,9 @@ model = AutoModelForCausalLM.from_pretrained(
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  torch_dtype=torch.bfloat16,
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  device_map="auto",
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  )
 
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  def completion(prompt: str, max_new_tokens: int = 128) -> str:
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  inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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  generated_ids = model.generate(
@@ -58,7 +61,7 @@ def generate_prompt(messages: list) -> str:
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  ]
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  roles = {"instruction": "指示", "response": "応答", "input": "入力"}
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  for msg in messages:
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- prompt.append(sep + roles[msg["role"]] + ":\n" + msg['content'])
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  prompt.append(sep + roles["response"] + ":\n")
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  return "".join(prompt)
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  ```
 
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  ## Usage
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  Install the required libraries as follows:
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  ```sh
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+ >>> python -m pip install numpy sentencepiece torch transformers accelerate
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  ```
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  Execute the following python code:
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  ```python
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+ import torch
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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  tokenizer = AutoTokenizer.from_pretrained(
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  "pfnet/plamo-13b-instruct",
 
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  torch_dtype=torch.bfloat16,
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  device_map="auto",
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  )
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+ ```
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+ ```python
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  def completion(prompt: str, max_new_tokens: int = 128) -> str:
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  inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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  generated_ids = model.generate(
 
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  ]
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  roles = {"instruction": "指示", "response": "応答", "input": "入力"}
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  for msg in messages:
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+ prompt.append(sep + roles[msg["role"]] + ":\n" + msg["content"])
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  prompt.append(sep + roles["response"] + ":\n")
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  return "".join(prompt)
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  ```