Instructions to use Jeevesh8/multiberts_seed_7_ft_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_7_ft_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_7_ft_3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_7_ft_3") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_7_ft_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Jeevesh8/multiberts_seed_7_ft_3: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Jeevesh8/multiberts_seed_7_ft_3/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Jeevesh8/multiberts_seed_7_ft_3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Jeevesh8/multiberts_seed_7_ft_3/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- cbca44952e56edaf6cf7e53912bd78c54ce3edacc841eec6193e7d811e04c110
- Size of remote file:
- 438 MB
- SHA256:
- 6863df129c0290271cdd8d9d3191878f242e4b52f70d1f6e548a8218df09eebb
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