Instructions to use kkkzzzkkk/example_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kkkzzzkkk/example_model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="kkkzzzkkk/example_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("kkkzzzkkk/example_model") model = AutoModelForQuestionAnswering.from_pretrained("kkkzzzkkk/example_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kkkzzzkkk/example_model: direct link, hf CLI and curl.
- Browser
- Download file 54 MB
-
https://huggingface.co/kkkzzzkkk/example_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kkkzzzkkk/example_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kkkzzzkkk/example_model/resolve/main/pytorch_model.bin
54 MB
- Xet hash:
- c23e97a17c7d8616b7cf5ff53ca78655bffa5b7b436e75bcbe4a65a5ce28b9f9
- Size of remote file:
- 54 MB
- SHA256:
- 4e3b4662fa04df79d9b7907c8d84a75dfd82c63c934827bf200eb376f808ba58
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.