35 lines
714 B
Plaintext
35 lines
714 B
Plaintext
# Step 1 (Run once)
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!pip install -U transformers
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# Step 2
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from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
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# Using pipeline
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pipe = pipeline("text-generation", model="sargurun16/VCoder")
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messages = [
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{"role": "user", "content": "Who are you?"},
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]
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print(pipe(messages))
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# Step 3 & 4
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model_name = "sargurun16/VCoder"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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prompt = "write a python code to merge 3 arrays"
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inputs = tokenizer(
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prompt,
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return_tensors="pt"
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)
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outputs = model.generate(
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**inputs,
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max_new_tokens=200
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)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(response) |