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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jitin/manglish") model = AutoModelForMaskedLM.from_pretrained("Jitin/manglish") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80e8a90eef89161fdf54a70deec83f83286d7d65995e7b8d39e321dfaf022866
- Size of remote file:
- 334 MB
- SHA256:
- 684cd3a266353885b893226ce776c8924132bb8967944e8c3988f05813860ff7
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