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--- |
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license: cc-by-nc-4.0 |
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--- |
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# Mixtral MOE 5x7B |
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MoE of the following models : |
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* [Toten5/Marcoroni-neural-chat-7B-v1](https://huggingface.co/Toten5/Marcoroni-neural-chat-7B-v1) |
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* [NurtureAI/neural-chat-7b-v3-16k](https://huggingface.co/NurtureAI/neural-chat-7b-v3-16k) |
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* [mncai/mistral-7b-dpo-v6](https://huggingface.co/mncai/mistral-7b-dpo-v6) |
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* [cookinai/CatMacaroni-Slerp](https://huggingface.co/cookinai/CatMacaroni-Slerp) |
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* [ignos/Mistral-T5-7B-v1](https://huggingface.co/ignos/Mistral-T5-7B-v1) |
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gpu code example |
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``` |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import math |
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## v2 models |
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model_path = "cloudyu/Mixtral_7Bx5_MoE_30B" |
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_path, torch_dtype=torch.float32, device_map='auto',local_files_only=False, load_in_4bit=True |
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) |
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print(model) |
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prompt = input("please input prompt:") |
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while len(prompt) > 0: |
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cuda") |
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generation_output = model.generate( |
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input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2 |
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) |
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print(tokenizer.decode(generation_output[0])) |
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prompt = input("please input prompt:") |
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``` |
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CPU example |
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``` |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import math |
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## v2 models |
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model_path = "cloudyu/Mixtral_7Bx5_MoE_30B" |
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_path, torch_dtype=torch.float32, device_map='cpu',local_files_only=False |
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) |
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print(model) |
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prompt = input("please input prompt:") |
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while len(prompt) > 0: |
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids |
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generation_output = model.generate( |
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input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2 |
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) |
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print(tokenizer.decode(generation_output[0])) |
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prompt = input("please input prompt:") |
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``` |