Instructions to use verloop/Hinglish-Bert-Class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use verloop/Hinglish-Bert-Class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="verloop/Hinglish-Bert-Class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("verloop/Hinglish-Bert-Class") model = AutoModelForSequenceClassification.from_pretrained("verloop/Hinglish-Bert-Class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from verloop/Hinglish-Bert-Class: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/verloop/Hinglish-Bert-Class/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://verloop/Hinglish-Bert-Class/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/verloop/Hinglish-Bert-Class/resolve/main/flax_model.msgpack
711 MB
- Xet hash:
- 56657bdb721fbe46cb5c50466660c7acf8bc7ad2108303c597fc42492539add3
- Size of remote file:
- 711 MB
- SHA256:
- 4b58d8468bd92c6c476a9c6e5f6a5d2e729c33caa38a1402d74295e37cfec989
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