Instructions to use microsoft/codebert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/codebert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/codebert-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/codebert-base") model = AutoModel.from_pretrained("microsoft/codebert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Add exported openvino model 'openvino_model_qint8_quantized.xml'
#7
by buelfhood - opened
openvino/openvino_model_qint8_quantized.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fa5a19365dbe5c7bc30d58f1a409ff4781434e047ad542eed2877d99f8fff252
|
| 3 |
+
size 125216864
|
openvino/openvino_model_qint8_quantized.xml
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|