Instructions to use slamos/bc-models-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slamos/bc-models-deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="slamos/bc-models-deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("slamos/bc-models-deberta") model = AutoModelForSequenceClassification.from_pretrained("slamos/bc-models-deberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model.onnx with huggingface_hub
Browse files- model.onnx +1 -1
model.onnx
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 740133121
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:21df6d6650b45bf325b8d8f0d58d778ae92f9b0a2f37c1310dba27fc578ee89c
|
| 3 |
size 740133121
|