Text Generation
Transformers
Chinese
English
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@@ -37,7 +37,7 @@ datasets:
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  >>> from transformers import AutoTokenizer, TextStreamer
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  >>> from auto_gptq import AutoGPTQForCausalLM
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  >>> tokenizer = AutoTokenizer.from_pretrained("fireballoon/baichuan-vicuna-chinese-7b-gptq", use_fast=False)
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- >>> model = AutoGPTQForCausalLM.from_pretrained("fireballoon/baichuan-vicuna-chinese-7b-gptq").cuda()
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  >>> streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
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  >>> instruction = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {} ASSISTANT:"
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  >>> prompt = instruction.format("How can I improve my time management skills?") # user message
 
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  >>> from transformers import AutoTokenizer, TextStreamer
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  >>> from auto_gptq import AutoGPTQForCausalLM
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  >>> tokenizer = AutoTokenizer.from_pretrained("fireballoon/baichuan-vicuna-chinese-7b-gptq", use_fast=False)
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+ >>> model = AutoGPTQForCausalLM.from_quantized("fireballoon/baichuan-vicuna-chinese-7b-gptq", device="cuda:0")
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  >>> streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
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  >>> instruction = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {} ASSISTANT:"
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  >>> prompt = instruction.format("How can I improve my time management skills?") # user message