Instructions to use raygx/GNePT-NepSA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raygx/GNePT-NepSA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raygx/GNePT-NepSA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("raygx/GNePT-NepSA") model = AutoModelForSequenceClassification.from_pretrained("raygx/GNePT-NepSA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from raygx/GNePT-NepSA: direct link, hf CLI and curl.
- Browser
- Download file 144 Bytes
-
https://huggingface.co/raygx/GNePT-NepSA/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://raygx/GNePT-NepSA/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/raygx/GNePT-NepSA/resolve/main/tokenizer_config.json
144 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "model_max_length": 512, | |
| "padding_side": "left", | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |