2023-05-25 08:11:43 +00:00
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# Example usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import transformers
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import torch
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model = "tiiuae/falcon-40B"
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tokenizer = AutoTokenizer.from_pretrained(model)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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torch_dtype=torch.bfloat16,
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trust_remote_code=True,
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device_map="auto",
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)
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sequences = pipeline(
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"My favourite dad joke is",
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2023-05-25 08:11:43 +00:00
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max_length=200,
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do_sample=True,
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top_k=10,
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num_return_sequences=1,
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eos_token_id=tokenizer.eos_token_id,
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)
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print("=" * 30)
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print("Results:")
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for seq in sequences:
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print(f"Result: {seq['generated_text']}")
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```
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