Instructions to use nilsho01/LittleNano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nilsho01/LittleNano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nilsho01/LittleNano")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nilsho01/LittleNano") model = AutoModelForMaskedLM.from_pretrained("nilsho01/LittleNano", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from nilsho01/LittleNano: direct link, hf CLI and curl.
- Browser
- Download file 107 Bytes
-
https://huggingface.co/nilsho01/LittleNano/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://nilsho01/LittleNano/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/nilsho01/LittleNano/resolve/main/tokenizer_config.json
107 Bytes
| { | |
| "model_max_length": 1000000000000000019884624838656, | |
| "tokenizer_class": "EsmTokenizer" | |
| } | |