--- language: - ko - en license: cc-by-nc-4.0 library_name: transformers tags: - mergekit - merge base_model: - Nexusflow/Athene-V2-Chat - Nexusflow/Athene-V2-Agent - anthracite-org/magnum-v4-72b - Qwen/Qwen2.5-72B-Instruct --- # spow12/MK_Nemo_12B ### Model Description This model is a Supervised fine-tuned version of [Qwen/Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) with DeepSpeed and trl for korean. Merge methods. ```yaml merge_method: model_stock name: ChatWaifu_72B_V2.4 models: - model: Nexusflow/Athene-V2-Chat - model: Nexusflow/Athene-V2-Agent - model: Qwen/Qwen2.5-72B-Instruct_instruction_tunned(private) - model: anthracite-org/magnum-v4-72b base_model: Qwen/Qwen2.5-72B-Instruct dtype: bfloat16 tokenizer_source: base ``` ### Trained Data - Trained with public, private data (about 500K) ### Usage ```python from transformers import TextStreamer, pipeline, AutoTokenizer, AutoModelForCausalLM model_id = 'spow12/KoQwen_72B_v5.0' tokenizer = AutoTokenizer.from_pretrained(model_id) # %% model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.bfloat16, attn_implementation="flash_attention_2", #Optional device_map='auto', ) model.eval() pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device_map='auto') generation_configs = dict( max_new_tokens=2048, num_return_sequences=1, temperature=0.75, # repetition_penalty=1.1, do_sample=True, top_k=20, top_p=0.9, min_p=0.1, eos_token_id=tokenizer.eos_token_id, pad_token_id=tokenizer.eos_token_id, streamer = TextStreamer(tokenizer) # Optional, if you want to use streamer, you have to set num_beams=1 ) sys_message = """당신은 친절한 챗봇으로서 상대방의 요청에 최대한 자세하고 친절하게 답해야합니다. 사용자가 제공하는 정보를 세심하게 분석하여 사용자의 의도를 신속하게 파악하고 그에 따라 답변을 생성해야합니다. 항상 매우 자연스러운 한국어로 응답하세요.""" message = [ { 'role': "system", 'content': sys_message }, { 'role': 'user', 'content': "현재의 경제상황에 대해 어떻게 생각해?." } ] conversation = pipe(message, **generation_configs) conversation[-1] ```