metastable-void commited on
Commit
10502ca
·
unverified ·
1 Parent(s): 59be267
Files changed (1) hide show
  1. app.py +3 -2
app.py CHANGED
@@ -24,6 +24,7 @@ if torch.cuda.is_available():
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  model_id = "vericava/llm-jp-3-1.8b-instruct-lora-vericava7-llama"
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  base_model_id = "llm-jp/llm-jp-3-1.8b-instruct"
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  tokenizer = AutoTokenizer.from_pretrained(base_model_id, trust_remote_code=True)
 
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  base_model = AutoModelForCausalLM.from_pretrained(
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  base_model_id,
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  trust_remote_code=True,
@@ -34,7 +35,6 @@ if torch.cuda.is_available():
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  model=model,
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  tokenizer=tokenizer,
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  )
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- my_pipeline.tokenizer.chat_template = "{{bos_token}}{% for message in messages %}{% if message['role'] == 'user' %}{{ '\\n\\n### 前の投稿:\\n' + message['content'] + '' }}{% elif message['role'] == 'system' %}{{ '以下は、SNS上の投稿です。あなたはSNSの投稿生成botとして、次に続く投稿を考えなさい。説明はせず、投稿の内容のみを鉤括弧をつけずに答えよ。' }}{% elif message['role'] == 'assistant' %}{{ '\\n\\n### 次の投稿:\\n' + message['content'] + eos_token }}{% endif %}{% if loop.last and add_generation_prompt %}{{ '\\n\\n### 次の投稿:\\n' }}{% endif %}{% endfor %}"
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  @spaces.GPU
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  @torch.inference_mode()
@@ -52,8 +52,9 @@ def generate(
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  {"role": "user", "content": message},
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  ]
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  output = my_pipeline(
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- messages,
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  )[-1]["generated_text"][-1]["content"]
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  yield output
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  model_id = "vericava/llm-jp-3-1.8b-instruct-lora-vericava7-llama"
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  base_model_id = "llm-jp/llm-jp-3-1.8b-instruct"
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  tokenizer = AutoTokenizer.from_pretrained(base_model_id, trust_remote_code=True)
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+ tokenizer.chat_template = "{{bos_token}}{% for message in messages %}{% if message['role'] == 'user' %}{{ '\\n\\n### 前の投稿:\\n' + message['content'] + '' }}{% elif message['role'] == 'system' %}{{ '以下は、SNS上の投稿です。あなたはSNSの投稿生成botとして、次に続く投稿を考えなさい。説明はせず、投稿の内容のみを鉤括弧をつけずに答えよ。' }}{% elif message['role'] == 'assistant' %}{{ '\\n\\n### 次の投稿:\\n' + message['content'] + eos_token }}{% endif %}{% if loop.last and add_generation_prompt %}{{ '\\n\\n### 次の投稿:\\n' }}{% endif %}{% endfor %}"
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  base_model = AutoModelForCausalLM.from_pretrained(
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  base_model_id,
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  trust_remote_code=True,
 
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  model=model,
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  tokenizer=tokenizer,
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  )
 
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  @spaces.GPU
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  @torch.inference_mode()
 
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  {"role": "user", "content": message},
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  ]
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+ t = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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  output = my_pipeline(
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+ t,
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  )[-1]["generated_text"][-1]["content"]
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  yield output
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