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- ---
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- license: cc-by-nc-sa-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+
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+
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+ ---
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+ license: cc-by-nc-sa-4.0
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+ language:
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+ - en
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+ - zh
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+ base_model:
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+ - Qwen/Qwen2.5-7B-Instruct
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+ tags:
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+ - machine tranlsation
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+ - O1-like model
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+ - Chat
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # DeepTrans-7B
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+
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+
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+ ## Quickstart
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+ - ⛷️ Huggingface Transformers:
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_name = "Krystalan/DeepTrans-7B"
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_name,
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+ torch_dtype="auto",
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+ device_map="auto"
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+
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+ prompt = "你是一个翻译专家,擅长将英文翻译成中文。你在翻译过程中非常擅长思考,会先进行思考再给出翻译结果。你的输出格式为:\n<think>\n[思考过程]\n</think>[翻译结果]\n\n在你思考完之后,也就是</think>之后,你会给出最终的翻译即“[翻译结果]”,且[翻译结果]中不需要给出任何解释和描述,只需要提供英文的翻译结果。\n现在请你翻译以下这句英语:\n" + "The mother, with her feet propped up on a stool, seemed to be trying to get to the bottom of that answer, whose feminine profundity had struck her all of a heap."
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+
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+ messages = [
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+ {"role": "user", "content": prompt}
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+ ]
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+ text = tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
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+ )
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+ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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+
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+ generated_ids = model.generate(
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+ **model_inputs,
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+ max_new_tokens=2048
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+ )
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+ generated_ids = [
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+ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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+ ]
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+
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+ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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+ print(response)
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+ ```
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+
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+ - ⛷️ vllm:
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+
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+ Deploying LLMs:
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+ ```bash
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+ python3 -m vllm.entrypoints.openai.api_server --model [model_ckpt] --served-model-name [model_name]
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+ ```
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+
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+ Calling LLMs:
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+ ```python
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+ from openai import OpenAI
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+ # Set OpenAI's API key and API base to use vLLM's API server.
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+ openai_api_key = "EMPTY"
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+ openai_api_base = "http://localhost:8000/v1"
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+
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+ client = OpenAI(
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+ api_key=openai_api_key,
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+ base_url=openai_api_base,
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+ )
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+
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+ prompt = "你是一个翻译专家,擅长将英文翻译成中文。你在翻译过程中非常擅长思考,会先进行思考再给出翻译结果。你的输出格式为:\n<think>\n[思考过程]\n</think>[翻译结果]\n\n在你思考完之后,也就是</think>之后,你会给出最终的翻译即“[翻译结果]”,且[翻译结果]中不需要给出任何解释和描述,只需要提供英文的翻译结果。\n现在请你翻译以下这句英语:\n" + "The mother, with her feet propped up on a stool, seemed to be trying to get to the bottom of that answer, whose feminine profundity had struck her all of a heap."
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+
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+ chat_response = client.chat.completions.create(
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+ model=[model_name],
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+ messages=[
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+ {"role": "user", "content": prompt},
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+ ],
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+ temperature=0.1,
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+ top_p=0.8,
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+ max_tokens=2048,
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+ extra_body={
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+ "repetition_penalty": 1.05,
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+ },
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+ )
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+ print("Chat response:", chat_response)
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+ ```
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+
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+
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+
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+ ## License
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+ This work is licensed under cc-by-nc-sa-4.0
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+
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+
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+