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--- |
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license: bigscience-openrail-m |
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--- |
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how to use |
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``` |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import textwrap, time |
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MAX_NEW_TOKENS = 300 |
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model_name = "acul3/bloomz-3b-Instruction" |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name, |
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device_map='auto', |
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load_in_8bit= True |
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) |
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def generate_text(text): |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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text = "User: " + text + "\n\Asisten: " |
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input_ids = tokenizer(text, return_tensors="pt").input_ids.to("cuda") |
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generated_ids = model.generate(input_ids, max_length=MAX_NEW_TOKENS, pad_token_id=tokenizer.eos_token_id, do_sample=True, top_p=0.95, temperature=0.5, penalty_alpha=0.6, top_k=4, repetition_penalty=1.03, num_return_sequences=1) |
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result = textwrap.wrap(tokenizer.decode(generated_ids[0], skip_special_tokens=True), width=128) |
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result[0] = result[0].split("Asisten:")[-1] |
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return "\n".join(result) |
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print(generate_text("cara merebus telur")) |
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``` |
