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--- |
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license: apache-2.0 |
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--- |
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``` |
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from transformers import AutoModelForCausalLM, AutoTokenizer, AutoModel |
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import torch |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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print(f"Using device: {device}") |
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model = AutoModelForCausalLM.from_pretrained("orionweller/test-flex-gpt", trust_remote_code=True) |
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model = model.to(device) |
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tokenizer = AutoTokenizer.from_pretrained("orionweller/test-flex-gpt", trust_remote_code=True) |
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# test it out and encode some text |
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prompt = "The capital of France is" |
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inputs = tokenizer(prompt, return_tensors="pt").input_ids |
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# put the input ids on the right device |
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inputs = inputs.to(device) |
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outputs = model.generate(inputs, max_new_tokens=5, do_sample=True, top_p=0.95) |
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print(tokenizer.batch_decode(outputs, skip_special_tokens=True)) |
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``` |
