Instructions to use Jeevesh8/DA-LF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/DA-LF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jeevesh8/DA-LF")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/DA-LF") model = AutoModelForMaskedLM.from_pretrained("Jeevesh8/DA-LF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeevesh8/DA-LF: direct link, hf CLI and curl.
- Browser
- Download file 595 MB
-
https://huggingface.co/Jeevesh8/DA-LF/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeevesh8/DA-LF/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeevesh8/DA-LF/resolve/main/pytorch_model.bin
595 MB
- Xet hash:
- 54f2dd976f5977518b1f220b90095d52954d7724511c0772b711d66683ce0bac
- Size of remote file:
- 595 MB
- SHA256:
- af8aa339833c8da3329e9d424286b08e2eb63325235a459d0ec0b43be2574ec0
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