Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Sadashiv/BERT-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sadashiv/BERT-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Sadashiv/BERT-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Sadashiv/BERT-ner") model = AutoModelForTokenClassification.from_pretrained("Sadashiv/BERT-ner") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2500
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 435661993
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:69ac0fc46ecc4fb87804062267c75c523801dc900cb6095bd10ad705d6670aa2
|
| 3 |
size 435661993
|
runs/Jul21_08-13-59_b31798a51a37/events.out.tfevents.1689927276.b31798a51a37.1201.1
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:51bd629ee5b8cae58ef4fc597afb1f4e632c58676f7683fe9d09abd7e58772c9
|
| 3 |
+
size 6164
|