Instructions to use handraise-dev/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use handraise-dev/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="handraise-dev/test-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("handraise-dev/test-model") model = AutoModelForSequenceClassification.from_pretrained("handraise-dev/test-model") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 2
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 711443456
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b7824a2bd6ee1e24f65f50e4d6632766b7826d0627b83ce0c9f4dfc176ae001a
|
| 3 |
size 711443456
|