Instructions to use krishnakalyan3/lit-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krishnakalyan3/lit-transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="krishnakalyan3/lit-transformers")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("krishnakalyan3/lit-transformers") model = AutoModelForSequenceClassification.from_pretrained("krishnakalyan3/lit-transformers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from krishnakalyan3/lit-transformers: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/krishnakalyan3/lit-transformers/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://krishnakalyan3/lit-transformers/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/krishnakalyan3/lit-transformers/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 5eed3da30c47207f447e86d51d4d2feff59027a268d63ec286f6b52936c7229d
- Size of remote file:
- 438 MB
- SHA256:
- 595f068e1c92a613fc96f3aa72ad5b2d40e290c0d3e867f2212bb38d1ee9de3c
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