Instructions to use devanshrj/scibert-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devanshrj/scibert-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="devanshrj/scibert-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("devanshrj/scibert-ner") model = AutoModelForTokenClassification.from_pretrained("devanshrj/scibert-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 163 Bytes
4c82c50 | 1 2 3 4 5 6 7 | {
"epoch": 1.0,
"train_loss": 0.437174129486084,
"train_runtime": 65.2493,
"train_samples_per_second": 14.606,
"train_steps_per_second": 0.92
} |