Instructions to use SoumyaRanjan/bert-pretrained-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SoumyaRanjan/bert-pretrained-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SoumyaRanjan/bert-pretrained-text-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SoumyaRanjan/bert-pretrained-text-classification") model = AutoModelForSequenceClassification.from_pretrained("SoumyaRanjan/bert-pretrained-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from SoumyaRanjan/bert-pretrained-text-classification: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/SoumyaRanjan/bert-pretrained-text-classification/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://SoumyaRanjan/bert-pretrained-text-classification/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/SoumyaRanjan/bert-pretrained-text-classification/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- 511491cd4e93146c5df6f80dcc8e537c085e73f211fb26fbaeb6b5a09e079730
- Size of remote file:
- 438 MB
- SHA256:
- ea201fabe466ef7182f1f687fb5be4b62a73d3a78883f11264ff7f682cdb54bf
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