Token Classification
Transformers
PyTorch
TensorBoard
electra
Generated from Trainer
Eval Results (legacy)
Instructions to use chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner") model = AutoModelForTokenClassification.from_pretrained("chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner: direct link, hf CLI and curl.
- Browser
- Download file 717 kB
-
https://huggingface.co/chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/chintagunta85/electramed-small-ADE-DRUG-DOSAGE-ner/resolve/refs%2Fpr%2F2/tokenizer.json
717 kB
File too large to display, you can check the raw version instead.