Update llm_inference.py
Browse files- llm_inference.py +3 -3
llm_inference.py
CHANGED
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@@ -184,7 +184,7 @@ Your output is only the caption itself, no comments or extra formatting. The cap
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response = self.huggingface_client.chat.completions.create(
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model=model or "meta-llama/Meta-Llama-3.1-70B-Instruct",
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max_tokens=1024,
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-
temperature=0
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top_p=0.95,
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messages=[
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{"role": "system", "content": system_message},
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@@ -198,7 +198,7 @@ Your output is only the caption itself, no comments or extra formatting. The cap
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response = self.groq_client.chat.completions.create(
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model=model or "llama-3.1-70b-versatile",
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max_tokens=1024,
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temperature=0
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messages=[
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{"role": "system", "content": system_message},
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{"role": "user", "content": user_message},
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@@ -211,7 +211,7 @@ Your output is only the caption itself, no comments or extra formatting. The cap
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response = self.sambanova_client.chat.completions.create(
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model=model or "Meta-Llama-3.1-70B-Instruct",
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max_tokens=1024,
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temperature=0
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messages=[
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{"role": "system", "content": system_message},
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{"role": "user", "content": user_message},
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response = self.huggingface_client.chat.completions.create(
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model=model or "meta-llama/Meta-Llama-3.1-70B-Instruct",
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max_tokens=1024,
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+
temperature=1.0,
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top_p=0.95,
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messages=[
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{"role": "system", "content": system_message},
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response = self.groq_client.chat.completions.create(
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model=model or "llama-3.1-70b-versatile",
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max_tokens=1024,
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+
temperature=1.0,
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messages=[
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{"role": "system", "content": system_message},
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{"role": "user", "content": user_message},
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response = self.sambanova_client.chat.completions.create(
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model=model or "Meta-Llama-3.1-70B-Instruct",
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max_tokens=1024,
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| 214 |
+
temperature=1.0,
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messages=[
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{"role": "system", "content": system_message},
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{"role": "user", "content": user_message},
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