Instructions to use Cournane/roberta-base-reduced-Hat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Hat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Hat", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Hat") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Hat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 2
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498662069
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5947cd917e4c57d3f5a41b29e768eaff1d0af62830dfe3698b6c4d2a8ec7e5d8
|
| 3 |
size 498662069
|