Instructions to use kumarme072/med_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kumarme072/med_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kumarme072/med_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kumarme072/med_model") model = AutoModelForMaskedLM.from_pretrained("kumarme072/med_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from kumarme072/med_model: direct link, hf CLI and curl.
- Browser
- Download file 125 Bytes
-
https://huggingface.co/kumarme072/med_model/resolve/refs%2Fpr%2F1/special_tokens_map.json
- Command line
-
hf download hf://kumarme072/med_model@refs/pr/1/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/kumarme072/med_model/resolve/refs%2Fpr%2F1/special_tokens_map.json
125 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |