Update README.md
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README.md
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@@ -23,16 +23,16 @@ Start chatting with `FreeWilly2` using the following code snippet:
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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tokenizer = AutoTokenizer.from_pretrained("stabilityai/FreeWilly2, use_fast=False)
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model = AutoModelForCausalLM.from_pretrained("stabilityai/FreeWilly2", torch_dtype=torch.float16, low_cpu_mem_usage=True,
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generator = pipeline(model=model, tokenizer=tokenizer)
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system_prompt = "### System:\nYou are Free Willy, an AI that follows instructions extremely well. Help as much as you can. Remember, be safe, and don't do anything illegal.\n\n"
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message = "Write me a poem please"
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prompt = f"{system_prompt}### User: {message}\n\n### Assistant:\n"
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output
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print(output)
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```
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FreeWilly should be used with this prompt format:
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@@ -102,4 +102,3 @@ Although the aforementioned dataset helps to steer the base language models into
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primaryClass={cs.CL}
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}
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```
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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tokenizer = AutoTokenizer.from_pretrained("stabilityai/FreeWilly2", use_fast=False)
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model = AutoModelForCausalLM.from_pretrained("stabilityai/FreeWilly2", torch_dtype=torch.float16, low_cpu_mem_usage=True, device_map="auto")
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system_prompt = "### System:\nYou are Free Willy, an AI that follows instructions extremely well. Help as much as you can. Remember, be safe, and don't do anything illegal.\n\n"
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message = "Write me a poem please"
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prompt = f"{system_prompt}### User: {message}\n\n### Assistant:\n"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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output = model.generate(**inputs, do_sample=True, top_p=0.95, top_k=0, max_new_tokens=256)
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print(tokenizer.decode(output[0], skip_special_tokens=True))
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```
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FreeWilly should be used with this prompt format:
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primaryClass={cs.CL}
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}
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```
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