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--- |
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license: llama3 |
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--- |
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finetuned by simplescaling/s1K |
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example code |
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```python |
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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/S1-Llama-3.2-3Bx4-MoE" |
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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, trust_remote_code=True,device_map='mps' |
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) |
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print(model) |
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print(model.lm_head.weight) |
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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("mps") |
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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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``` |