|
--- |
|
license: apache-2.0 |
|
datasets: |
|
- KingNish/reasoning-base-20k |
|
language: |
|
- en |
|
- zh |
|
base_model: |
|
- Qwen/Qwen2.5-1.5B |
|
--- |
|
|
|
## Uses |
|
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
|
model_name = "/root/app/Reason/checkpoints" |
|
|
|
model = AutoModelForCausalLM.from_pretrained( |
|
model_name, |
|
torch_dtype="auto", |
|
device_map="auto" |
|
) |
|
tokenizer = AutoTokenizer.from_pretrained(model_name) |
|
|
|
from typing import List, Dict |
|
def new_apply_chat_template(history:List[Dict[str, str]], add_reasoning_generation_prompt:bool=True, add_assistant_generation_prompt:bool=False): |
|
if add_reasoning_generation_prompt: |
|
return "".join([f"<|im_start|>{i['role']}\n{i['content']}<|im_end|>\n" for i in history]) + "<|im_start|><|reasoning|>\n" |
|
if add_assistant_generation_prompt: |
|
return "".join([f"<|im_start|>{i['role']}\n{i['content']}<|im_end|>\n" for i in history]) + "<|im_start|>assistant\n" |
|
|
|
|
|
from IPython.display import Markdown, display |
|
device = "cuda" |
|
history = [] |
|
history.append({"role": "system", "content": "You are a helpful assistant"}) |
|
while True: |
|
question = input('User：' + '\n') |
|
print(question) |
|
print('\n') |
|
history.append({"role": "user", "content": question}) |
|
|
|
input_text = new_apply_chat_template( |
|
history, |
|
add_reasoning_generation_prompt=True |
|
) |
|
model_inputs = tokenizer([input_text], return_tensors="pt").to(device) |
|
|
|
if model_inputs.input_ids.size()[1]>32000: |
|
break |
|
|
|
generated_ids = model.generate( |
|
model_inputs.input_ids, |
|
max_new_tokens=3000 |
|
) |
|
|
|
if len(generated_ids)>32000: |
|
break |
|
|
|
generated_ids = [output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)] |
|
|
|
reasoning_response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
|
history.append({"role": "<|reasoning|>", "content": reasoning_response}) |
|
print('reasoning:\n') |
|
#print(response) |
|
display(Markdown(reasoning_response)) |
|
print("------------") |
|
print('\n') |
|
|
|
input_text = new_apply_chat_template( |
|
history, |
|
add_assistant_generation_prompt=True |
|
) |
|
model_inputs = tokenizer([input_text], return_tensors="pt").to(device) |
|
|
|
if model_inputs.input_ids.size()[1]>32000: |
|
break |
|
|
|
generated_ids = model.generate( |
|
model_inputs.input_ids, |
|
max_new_tokens=3000 |
|
) |
|
|
|
if len(generated_ids)>32000: |
|
break |
|
|
|
generated_ids = [output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)] |
|
|
|
assistant_response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
|
history.append({"role": "assistant", "content": assistant_response}) |
|
print('assistant:\n') |
|
display(Markdown(assistant_response)) |
|
print("------------") |
|
|
|
print("超过模型字数上线，已退出") |
|
|
|
|
|
|
|
|
