huggingface-cli login Once you have logged in your terminal, now you can push your model to hugging face using below line. model.push_to_hub("my-awesome-model") But if you have not defined any arguments then it will give error.Please go through this link https://...
Notably, the sub folders in the hub/ directory are also named similar to the cloned model path, instead of having a SHA hash, as in previous versions. Update 2021-03-11: The cache location has now changed, and is located in ~/.cache/huggingface/transformers, as it is also detailed in ...
huggingfacedeleted a comment fromgithub-actionsbotJul 6, 2023 Contributor younesbelkadacommentedAug 17, 2023 👀3nlpcat, majid999, and kbulutozler reacted with eyes emoji 👀 nathan-azmentioned this issueAug 28, 2023 Is there any way to save models trained with 4 bit quantization?TimDettmers...
padding="longest") # Will pad the sequences up to the model max length # (512 for BERT or DistilBERT) model_inputs = tokenizer(sequences, padding="max_length") # Will pad the sequences up to the specified max length model_inputs = tokenizer(sequences, padding=...
Source:https://huggingface.co/transformers/model_sharing.html Should I save the model parameters separately, save the BERT first and then save my own nn.linear. Is this the only way to do the above? Is there an easy way? Thank you for your reply ...
"huggingface-hub==0.19.4", "idna==3.4", "imageio==2.33.0", "importlib-metadata==7.0.0", "importlib-resources==6.1.1", "inflection==0.5.1", "iopath==0.1.9", "jinja2==3.1.2", "jsonmerge==1.8.0", "jsonschema-specifications==2023.11.2", "jsonschema==4.20.0", "kiwisolver==1.4...
Huggingface_hub version: 0.16.4 Safetensors version: 0.3.1 PyTorch version (GPU?): 2.0.1+cu117 (True) Tensorflow version (GPU?): not installed (NA) Flax version (CPU?/GPU?/TPU?): not installed (NA) Jax version: not installed
cpu_ids = [id(v) for v in model.parameters()] # TODO: enable self.device (if needed). model = self.state.tp_plugin.parallelize_model(model, device=None) if os.environ.get("XLA_USE_BF16", "0") == "1" or os.environ.get("XLA_DOWNCAST_BF16", "0") == "1": model.to(tor...
Saving 4bit Bitsandbytes model. Please wait...") pass # Update model tag _ = upload_to_huggingface( model, save_directory, token, "finetuned", "trl", file_location = None, old_username = None, private = private, ) getattr(model, "original_push_to_hub", tokenizer.push_to_hub)\ ...
The model weights are not tied. Please use the `tie_weights` method before using the `infer_auto_device` f unction. The safetensors archive passed at /home/austin/.cache/huggingface/hub/models--TheBloke--WizardLM-7B-V1.0-U ncensored-GPTQ/snapshots/7060367aea53b1686be0c52962bc0405cfba...