Instructions to use Jeevesh8/multiberts_seed_17_ft_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_17_ft_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_17_ft_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_17_ft_2") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_17_ft_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Jeevesh8/multiberts_seed_17_ft_2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Jeevesh8/multiberts_seed_17_ft_2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Jeevesh8/multiberts_seed_17_ft_2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Jeevesh8/multiberts_seed_17_ft_2/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- 030f2e7a9448f3a555b8ff08d9ee62a786e238ce1d1cd788856b0ed737ccc12c
- Size of remote file:
- 438 MB
- SHA256:
- ed3a4778708aad70dde7aeebc49acf15f5e3a15468e6584b9e5d82cd741f6037
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