Instructions to use skillzzzzzy/hindberto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skillzzzzzy/hindberto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="skillzzzzzy/hindberto")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("skillzzzzzy/hindberto") model = AutoModelForMaskedLM.from_pretrained("skillzzzzzy/hindberto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from skillzzzzzy/hindberto: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/skillzzzzzy/hindberto/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://skillzzzzzy/hindberto/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/skillzzzzzy/hindberto/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 39c0a2372a8b663b1bc9fc1e654a11430b1ce4deeae09d567ab93915ad6f8e39
- Size of remote file:
- 268 MB
- SHA256:
- e4294051dd7d2163e08fc065ce395e52689df60d5805efc60aabc4ba766efc66
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.