Instructions to use nirantk/hinglish-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nirantk/hinglish-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nirantk/hinglish-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nirantk/hinglish-bert") model = AutoModelForMaskedLM.from_pretrained("nirantk/hinglish-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (7569a145d839064b00ebaaaed45c6dacafd494fc) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>a964b2b
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allow flax
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initial commit
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