Instructions to use Cube/cubetest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cube/cubetest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Cube/cubetest")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Cube/cubetest") model = AutoModelForMaskedLM.from_pretrained("Cube/cubetest") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5c3cb3b8e5b60164a1de2b34cdcf04bda7b4e27a00212785069b6058509ad3a7
|
| 3 |
+
size 411614051
|