尝试使用trainer.save_model(model_path)保存模型预计在使用 trainer.save_model(model_path) 保存模型时,将保存包括 model.bin 在内的所有必需文件。观察到只保存了training_args.bin、model.safetensors和config.json文件,而没有包含model.bin。huggingface-transformers huggingface fine-tuning huggingface-trainer 1...
wejoncy changed the title Skip collecting duplicated weight [save_pretrained ] Skip collecting duplicated weight Feb 26, 2025 format 3d5108e Member gante commented Feb 26, 2025 Hi @wejoncy 👋 I'm not a reviewer for this PR, but I can foresee a request: please share with us a script...
if True: model.save_pretrained_gguf("model", tokenizer,) Save to 16bit GGUF if False: model.save_pretrained_gguf("model_f16", tokenizer, quantization_method = "f16") Save to q4_k_m GGUF if False: model.save_pretrained_gguf("model", tokenizer, quantization_method = "q4_k_m") Un...
看了下问题,目前save_pretrained接口还不支持模型的attribute为非ErnieModel的网络。 所以ErnieCrfForTokenClassification不支持使用save_pretrained进行model_config.json的保存。 建议直接保存只需要保存模型参数,使用paddle.save(model.state_dict(), "/path/to/model") 预测时,有两个建议方法: 先用from_pretrained初始...
如果需要保存tensorflow版本的量化模型,则在 model.save_pretrained 中将参数 safe_serialization 置为 True如果需要保存pytorch版本,则置为False#人工智能 #AI #AI技术 #LLM #LLM (大型语言模型) #GPT #Python #PyTorch #TensorFlow 学习#深度学习 (Deep Learning)#大模型 #大语言模型...
感觉huggingface的接口也不合理 | 感觉huggingface的save pretrain和from pretrained接口把代码和weights搅在一起很不合理。。。code是表示网络结构的,weight是表示网络参数的,这俩还是应该解耦开。 发布于 2025-01-06 01:26・IP 属地北京 赞同 分享收藏 ...
Based on the introduction, one bin model can be saved by changing the "max_shard_size". LlamaForCausalLM.save_pretrained(base_model, output_dir, max_shard_size="100GB")# save one binifthe model is less than 100GB Reference PreTrainedModel...
config = BitsAndBytesConfig( load_in_8bit=True, ) path ="/home/llm/model/path/"model = AutoModelForCausalLM.from_pretrained(path, device_map="cpu", quantization_config=config) model.save_pretrained("model_save_folder-8bit")
When using from_pretrained without device_map="auto" the model is completely loaded into CPU RAM and also completely saved using save_pretrained. Checking the file sizes in the custom path chunk 1 to 4 have the expected 10GB and chunk5 has the expected 6GB. Same file sizes as in the Tra...
My System Info peft==0.4.0 accelerate==0.18.0 transformers==4.28.0 py310 Reproduction After training, I merge the peft weights with base model using: model_ft = PeftModel.from_pretrained( AutoModelForCausalLM.from_pretrained( base_model_...