save_pretrained 4-bit models with bitsandbytes westnopened this issueMay 31, 2023· 11 comments huggingfacedeleted a comment fromgithub-actionsbotJul 6, 2023 Contributor younesbelkadacommentedAug 17, 2023 👀3nlpcat, majid999, and kbulutozler reacted with eyes emoji...
Here is the code of loading quantized model: bnb_config = transformers.BitsAndBytesConfig( load_in_4bit=True, bnb_4bit_quant_type='nf4', bnb_4bit_use_double_quant=True, bnb_4bit_compute_dtype=bfloat16 ) hf_auth = '*' model_config = transformers.AutoConfig.from_...
bert_model = TFBertModel.from_pretrained('./Fine_tune_BERT/') But do i need to saver the tokenizer too? Or could I just use it in the normal way like: tokenizer = BertTokenizer.from_pretrained('bert-base-cased') bert-language-model huggingface-transformers Share Improve this question...
Checkpoint saving broken with the latest version of huggingfacejohnsmith0031/alpaca_lora_4bit#135 Closed Running123mentioned this issueJul 22, 2023 The issue is with these lines ofcode. It messes with the model state_dict, so the second time it's called from the save_pretrained() method it...
调用from_pretrained函数后,权重会被自动下载和缓存,默认存放目录为~/.cache/huggingface/transformers。可以通过设置HF_HOME环境变量来设置缓存目录。 上述from_pretrained方法中的模型可以在Model Hub中找到,可以用来加载所有使用BERT架构的checkpoint。完整的BERT checkpoint列表可以在链接here中找到。 保存模型 保存模型像加...
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...
I have created my own BertClassifier model, starting from a pretrained and then added my own classification heads composed by different layers. After the fine-tuning, I want to save the model using model.save_pretrained() but when I print it upload it from pretrained i don't s...
I've tried save model via: ppo_trainer.save_pretrained("./model_after_rl") and load the model via: model = AutoModelForCausalLMWithValueHead.from_pretrained("./model_after_rl") ref_model = AutoModelForCausalLMWithValueHead.from_pretraine...
fromtransformersimportAutoTokenizertok=AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1",add_special_tokens=True)tok.save_pretrained("out") The snippet: works well onadd_special_tokens=being present, absent, True/False on 4.33 and below ...
python huggingface-transformers Share Improve this question Follow edited Apr 26 at 15:44 asked Apr 26 at 15:34 miguelik 52566 silver badges1212 bronze badges Add a comment 1 Answer Sorted by: 0 You can try: model.save_pretrained(output_dir, safe_serialization=False) ...