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--- |
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library_name: transformers |
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license: apache-2.0 |
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datasets: |
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- Vikhrmodels/GrandMaster-PRO-MAX |
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language: |
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- ru |
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base_model: |
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- HuggingFaceTB/SmolLM2-360M-Instruct |
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pipeline_tag: text-generation |
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--- |
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v1: SFT -- 7658aab7702e56d9f5fa3b33bf7adcdae92f536b |
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```python |
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rom transformers import AutoModelForCausalLM, AutoTokenizer |
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checkpoint = "HuggingFaceTB/SmolLM2-360M-Instruct" |
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device = "cuda" # for GPU usage or "cpu" for CPU usage |
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tokenizer = AutoTokenizer.from_pretrained(checkpoint) |
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# for multiple GPUs install accelerate and do `model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="auto")` |
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model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device) |
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messages = [{"role": "user", "content": "What is the capital of France."}] |
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input_text=tokenizer.apply_chat_template(messages, tokenize=False) |
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print(input_text) |
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inputs = tokenizer.encode(input_text, return_tensors="pt").to(device) |
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outputs = model.generate(inputs, max_new_tokens=50, temperature=0.2, top_p=0.9, do_sample=True) |
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print(tokenizer.decode(outputs[0])) |
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``` |
