Text Classification
Transformers
PyTorch
TensorFlow
TensorBoard
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use thomasavare/distilbert-ft-test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thomasavare/distilbert-ft-test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thomasavare/distilbert-ft-test1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thomasavare/distilbert-ft-test1") model = AutoModelForSequenceClassification.from_pretrained("thomasavare/distilbert-ft-test1") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:9159d6c1f081bb2a3e8fe0315b50f0885d83684019d6b078b2c2baa943a14d7d
|
| 3 |
+
size 328496480
|