Instructions to use opticalmaterials/opticalbert_abstract_classification_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opticalmaterials/opticalbert_abstract_classification_cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="opticalmaterials/opticalbert_abstract_classification_cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("opticalmaterials/opticalbert_abstract_classification_cased") model = AutoModelForSequenceClassification.from_pretrained("opticalmaterials/opticalbert_abstract_classification_cased") - Notebooks
- Google Colab
- Kaggle
Commit ·
756d7a9
1
Parent(s): 4967013
Upload training_args.bin
Browse files- training_args.bin +3 -0
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a805ba5894dac301d49f059499421b6a2a189af308023bc93fa101d191c40e4c
|
| 3 |
+
size 3247
|