Instructions to use Jitin/manglish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jitin/manglish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jitin/manglish")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jitin/manglish") model = AutoModelForMaskedLM.from_pretrained("Jitin/manglish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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upload flax model
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allow flax
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LM iteration of manglish config
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Third iteration of manglish model and tokenizer
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Second iteration of manglish model and tokenizer
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First iteration of manglish model and tokenizer
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initial commit
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