Instructions to use debajyotidatta/eduopt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use debajyotidatta/eduopt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="debajyotidatta/eduopt")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("debajyotidatta/eduopt") model = AutoModelForSequenceClassification.from_pretrained("debajyotidatta/eduopt", 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 sha256:3a4912b1aac8d677e1954e9dd61bcd5e0fb3eb0f27f8f2e1570f5d95709c1dc7
|
| 3 |
+
size 1324841208
|