Instructions to use rwillh11/base-mdbertav3-token-classification-groups-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rwillh11/base-mdbertav3-token-classification-groups-2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rwillh11/base-mdbertav3-token-classification-groups-2.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rwillh11/base-mdbertav3-token-classification-groups-2.0") model = AutoModelForTokenClassification.from_pretrained("rwillh11/base-mdbertav3-token-classification-groups-2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a45c380c31027d8d6fa63c8cd93a6a982c265c8614abc025d74f033c1dd8dbb7
|
| 3 |
+
size 1112905648
|