ce6d06eb0a
* Support directly quantizing huggingface transformers into 4bit format * refine example * license * fix bias * address comments * move to ggml transformers * fix example * fix style * fix style * address comments * rename * change API * fix style * add lm head to conversion * address comments
36 lines
1.4 KiB
Python
36 lines
1.4 KiB
Python
#
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# Copyright 2016 The BigDL Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import torch
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import os
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from bigdl.llm.transformers import AutoModelForCausalLM
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from transformers import LlamaTokenizer
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if __name__ == '__main__':
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model_path = 'decapoda-research/llama-7b-hf'
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# load_in_4bit=True in bigdl.llm.transformers will convert
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# the relevant layers in the model into int4 format
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model = AutoModelForCausalLM.from_pretrained(model_path, load_in_4bit=True)
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tokenizer = LlamaTokenizer.from_pretrained(model_path)
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input_str = "Once upon a time, there existed a little girl who liked to have adventures. She wanted to go to places and meet new people, and have fun"
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with torch.inference_mode():
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input_ids = tokenizer.encode(input_str, return_tensors="pt")
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output = model.generate(input_ids, do_sample=False, max_new_tokens=32)
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output_str = tokenizer.decode(output[0], skip_special_tokens=True)
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print(output_str)
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