Instructions to use codingJacob/distilbert-base-uncased-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codingJacob/distilbert-base-uncased-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="codingJacob/distilbert-base-uncased-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("codingJacob/distilbert-base-uncased-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("codingJacob/distilbert-base-uncased-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#3
by librarian-bot - opened
README.md
CHANGED
|
@@ -23,6 +23,7 @@ model_index:
|
|
| 23 |
name: Accuracy
|
| 24 |
type: accuracy
|
| 25 |
value: 0.9843042559613643
|
|
|
|
| 26 |
---
|
| 27 |
|
| 28 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
|
| 23 |
name: Accuracy
|
| 24 |
type: accuracy
|
| 25 |
value: 0.9843042559613643
|
| 26 |
+
base_model: distilbert-base-uncased
|
| 27 |
---
|
| 28 |
|
| 29 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|