Instructions to use monsoon-nlp/tamillion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monsoon-nlp/tamillion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="monsoon-nlp/tamillion")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("monsoon-nlp/tamillion") model = AutoModel.from_pretrained("monsoon-nlp/tamillion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22aedb5a95d71e4cbc0e86c56a46d992a51f028d207d6da7689e916d06e5b06a
- Size of remote file:
- 467 MB
- SHA256:
- 1d51e553e733143d2328f739e76a8ad3e5e64aa4f0e12ff8db169260ec9ec0a6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.