Instructions to use hf-internal-testing/tiny-random-onnx-convbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-onnx-convbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-onnx-convbert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-onnx-convbert") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-onnx-convbert") - Notebooks
- Google Colab
- Kaggle
[Awaiting approval] Upload ONNX weights
#1
by Xenova HF Staff - opened
- onnx/model.onnx +3 -0
onnx/model.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f211f9d51ac1006fcc063b88957bae9ac4116377ba01d8111d8617d5dc1f7c5d
|
| 3 |
+
size 95774160
|