Instructions to use hossamamer12/MB2_1090C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hossamamer12/MB2_1090C with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hossamamer12/MB2_1090C")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hossamamer12/MB2_1090C") model = AutoModelForSequenceClassification.from_pretrained("hossamamer12/MB2_1090C", 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 sha256:01d2f0a150838c8bef9a73906246ae4eb48e31f7d20b14f8f2fc404f9e9086c3
|
| 3 |
+
size 12915128
|