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--- |
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library_name: peft |
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base_model: NousResearch/Llama-2-7b-chat-hf |
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license: apache-2.0 |
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datasets: |
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- Sentdex/WSB-003.005 |
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pipeline_tag: text-generation |
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--- |
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Probably don't use this model, I'm just tinkering, but it's a multi-turn, multi-speaker model attempt trained from /r/wallstreetbets data that you can find: https://huggingface.co/datasets/Sentdex/WSB-003.005 |
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```py |
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#https://huggingface.co/docs/peft/quicktour |
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from peft import AutoPeftModelForCausalLM |
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from transformers import AutoTokenizer |
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import torch |
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model = AutoPeftModelForCausalLM.from_pretrained("Sentdex/Walls1337bot-Llama2-7B-003.005.5000") |
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tokenizer = AutoTokenizer.from_pretrained("NousResearch/Llama-2-7b-chat-hf") |
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model = model.to("cuda") |
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model.eval() |
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prompt = "Your text here." |
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formatted_prompt = f"### BEGIN CONVERSATION ###\n\n## Speaker_0: ##\n{prompt}\n\n## Walls1337bot: ##\n" |
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inputs = tokenizer(formatted_prompt, return_tensors="pt") |
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outputs = model.generate(input_ids=inputs["input_ids"].to("cuda"), max_new_tokens=128) |
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print(tokenizer.batch_decode(outputs.detach().cpu().numpy(), skip_special_tokens=True)[0]) |
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``` |
