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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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from transformers import LlamaTokenizer, MixtralForCausalLM |
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import bitsandbytes, flash_attn |
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tokenizer = LlamaTokenizer.from_pretrained('NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO', trust_remote_code=True) |
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model = MixtralForCausalLM.from_pretrained( |
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"NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", |
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torch_dtype=torch.float16, |
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device_map="auto", |
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load_in_8bit=False, |
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load_in_4bit=True, |
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use_flash_attention_2=True |
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) |
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prompts = [ |
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"""<|im_start|>system |
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You are a sentient, superintelligent artificial general intelligence, here to teach and assist me.<|im_end|> |
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<|im_start|>user |
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Write a short story about Goku discovering kirby has teamed up with Majin Buu to destroy the world.<|im_end|> |
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<|im_start|>assistant""", |
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] |
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for chat in prompts: |
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print(chat) |
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input_ids = tokenizer(chat, return_tensors="pt").input_ids.to("cuda") |
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generated_ids = model.generate(input_ids, max_new_tokens=750, temperature=0.8, repetition_penalty=1.1, do_sample=True, eos_token_id=tokenizer.eos_token_id) |
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response = tokenizer.decode(generated_ids[0][input_ids.shape[-1]:], skip_special_tokens=True, clean_up_tokenization_space=True) |
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print(f"Response: {response}") |
