Instructions to use HealthNLP/pubmedbert_conmod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HealthNLP/pubmedbert_conmod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HealthNLP/pubmedbert_conmod")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HealthNLP/pubmedbert_conmod") model = AutoModelForSequenceClassification.from_pretrained("HealthNLP/pubmedbert_conmod", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from HealthNLP/pubmedbert_conmod: direct link, hf CLI and curl.
- Browser
- Download file 141 Bytes
-
https://huggingface.co/HealthNLP/pubmedbert_conmod/resolve/main/added_tokens.json
- Command line
-
hf download hf://HealthNLP/pubmedbert_conmod/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/HealthNLP/pubmedbert_conmod/resolve/main/added_tokens.json
141 Bytes
| { | |
| "</a1>": 28898, | |
| "</a2>": 28900, | |
| "</e>": 28896, | |
| "<a1>": 28897, | |
| "<a2>": 28899, | |
| "<cr>": 28901, | |
| "<e>": 28895, | |
| "<neg>": 28902 | |
| } | |