Upload predict.py with huggingface_hub
Browse files- predict.py +33 -4
predict.py
CHANGED
@@ -185,6 +185,8 @@ def get_conversation_template(model_path: str) -> Conversation:
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"""Get the default conversation template."""
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if "aquila-v1" in model_path:
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return get_conv_template("aquila-v1")
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elif "aquila-chat" in model_path:
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return get_conv_template("aquila-chat")
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elif "aquila-legacy" in model_path:
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@@ -252,6 +254,21 @@ register_conv_template(
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)
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)
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if __name__ == "__main__":
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print("aquila template:")
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@@ -294,6 +311,17 @@ if __name__ == "__main__":
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print("\n")
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def set_random_seed(seed):
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"""Set random seed for reproducability."""
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if seed is not None and seed > 0:
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@@ -330,9 +358,9 @@ def covert_prompt_to_input_ids_with_history(text, history, tokenizer, max_token,
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return example
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def predict(model, text, tokenizer=None,
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max_gen_len=200, top_p=0.
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seed=
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temperature=0
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sft=True, convo_template = "",
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device = "cuda",
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model_name="AquilaChat2-7B",
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@@ -346,6 +374,7 @@ def predict(model, text, tokenizer=None,
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template_map = {"AquilaChat2-7B": "aquila-v1",
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"AquilaChat2-34B": "aquila-legacy",
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"AquilaChat2-7B-16K": "aquila",
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"AquilaChat2-34B-16K": "aquila"}
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if not convo_template:
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@@ -356,7 +385,7 @@ def predict(model, text, tokenizer=None,
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topk = 1
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temperature = 1.0
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if sft:
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tokens = covert_prompt_to_input_ids_with_history(text, history=history, tokenizer=tokenizer, max_token=
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tokens = torch.tensor(tokens)[None,].to(device)
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else :
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tokens = tokenizer.encode_plus(text)["input_ids"]
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"""Get the default conversation template."""
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if "aquila-v1" in model_path:
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return get_conv_template("aquila-v1")
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+
elif "aquila-v2" in model_path:
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return get_conv_template("aquila-v2")
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elif "aquila-chat" in model_path:
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return get_conv_template("aquila-chat")
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elif "aquila-legacy" in model_path:
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)
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)
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register_conv_template(
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Conversation(
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name="aquila-v2",
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system_message="A chat between a curious human and an artificial intelligence assistant. "
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"The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
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roles=("<|startofpiece|>", "<|endofpiece|>", ""),
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messages=(),
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offset=0,
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sep_style=SeparatorStyle.NO_COLON_TWO,
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sep="",
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sep2="</s>",
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stop_str=["</s>", "<|endoftext|>", "<|startofpiece|>", "<|endofpiece|>"],
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)
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)
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if __name__ == "__main__":
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print("aquila template:")
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print("\n")
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print("aquila-v2 template:")
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conv = get_conv_template("aquila-v2")
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conv.append_message(conv.roles[0], "Hello!")
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conv.append_message(conv.roles[1], "Hi!")
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conv.append_message(conv.roles[0], "How are you?")
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conv.append_message(conv.roles[1], None)
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print(conv.get_prompt())
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print("\n")
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def set_random_seed(seed):
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"""Set random seed for reproducability."""
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if seed is not None and seed > 0:
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return example
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def predict(model, text, tokenizer=None,
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max_gen_len=200, top_p=0.9,
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seed=123, topk=15,
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temperature=1.0,
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sft=True, convo_template = "",
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device = "cuda",
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model_name="AquilaChat2-7B",
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template_map = {"AquilaChat2-7B": "aquila-v1",
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"AquilaChat2-34B": "aquila-legacy",
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"AquilaChat2-70B-Expr": "aquila-v2",
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"AquilaChat2-7B-16K": "aquila",
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"AquilaChat2-34B-16K": "aquila"}
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if not convo_template:
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topk = 1
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temperature = 1.0
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if sft:
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tokens = covert_prompt_to_input_ids_with_history(text, history=history, tokenizer=tokenizer, max_token=20480, convo_template=convo_template)
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tokens = torch.tensor(tokens)[None,].to(device)
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else :
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tokens = tokenizer.encode_plus(text)["input_ids"]
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