Instructions to use Kamer/Day2Best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kamer/Day2Best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kamer/Day2Best")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kamer/Day2Best") model = AutoModelForSequenceClassification.from_pretrained("Kamer/Day2Best") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 5000
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 438264945
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b114d8e1b902f8e1b5fb5c1a86996cf0fe5b2efe0a4085c34f62d722378aebed
|
| 3 |
size 438264945
|