初始化项目，由ModelHub XC社区提供模型
Model: Mr-Vicky-01/qwen-conversational-finetuned Source: Original Platform
This commit is contained in:
ModelHub XC
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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88
README.md
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README.md
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---
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base_model: unsloth/qwen2.5-0.5b-instruct-bnb-4bit
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen2
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- trl
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- sft
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license: apache-2.0
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language:
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- en
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---
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## INFERENCE
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```python
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# Load model directly
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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tokenizer = AutoTokenizer.from_pretrained("Mr-Vicky-01/qwen-conversational-finetuned")
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model = AutoModelForCausalLM.from_pretrained("Mr-Vicky-01/qwen-conversational-finetuned")
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prompt = """
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<|im_start|>system\nYou are a helpful AI assistant named Securitron<|im_end|>
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"""
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# Keep a list for the last one conversation exchanges
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conversation_history = []
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while True:
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user_prompt = input("\nUser Question: ")
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if user_prompt.lower() == 'break':
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break
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# Format the user's input
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user = f"""<|im_start|>user
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{user_prompt}<|im_end|>
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<|im_start|>assistant"""
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# Add the user's question to the conversation history
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conversation_history.append(user)
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# Ensure conversation starts with a user's input and keep only the last 2 exchanges (4 turns)
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conversation_history = conversation_history[-5:]
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# Build the full prompt
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current_prompt = prompt + "\n".join(conversation_history)
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# Tokenize the prompt
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encodeds = tokenizer(current_prompt, return_tensors="pt", truncation=True).input_ids
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# Move model and inputs to the appropriate device
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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model.to(device)
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inputs = encodeds.to(device)
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# Create an empty list to store generated tokens
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generated_ids = inputs
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# Start generating tokens one by one
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assistant_response = ""
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for _ in range(512): # Specify a max token limit for streaming
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next_token = model.generate(
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generated_ids,
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max_new_tokens=1,
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pad_token_id=151644,
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eos_token_id=151645,
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num_return_sequences=1,
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do_sample=False,
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# top_k=5,
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# temperature=0.2,
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# top_p=0.90
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)
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generated_ids = torch.cat([generated_ids, next_token[:, -1:]], dim=1)
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token_id = next_token[0, -1].item()
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token = tokenizer.decode([token_id], skip_special_tokens=True)
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assistant_response += token
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print(token, end="", flush=True)
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if token_id == 151645: # EOS token
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break
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conversation_history.append(f"{assistant_response.strip()}<|im_end|>")
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```
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25
added_tokens.json
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added_tokens.json
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32
config.json
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config.json
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{
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"_name_or_path": "unsloth/qwen2.5-0.5b-instruct-bnb-4bit",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"hidden_act": "silu",
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}
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15
generation_config.json
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"top_p": 0.8,
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151388
merges.txt
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model.safetensors
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special_tokens_map.json
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3
tokenizer.json
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217
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|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|PAD_TOKEN|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user