Instructions to use Mikask/bdc2024-tpg-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mikask/bdc2024-tpg-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mikask/bdc2024-tpg-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mikask/bdc2024-tpg-3") model = AutoModelForSequenceClassification.from_pretrained("Mikask/bdc2024-tpg-3", 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:b0c7c814db57efa56578c98c72ab307a2c79e9f6f41e43fb095bf30c989e8c93
|
| 3 |
+
size 466304720
|