Instructions to use yazansh/nuha-multiclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yazansh/nuha-multiclass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yazansh/nuha-multiclass")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yazansh/nuha-multiclass") model = AutoModelForSequenceClassification.from_pretrained("yazansh/nuha-multiclass", 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 sha256:4fcf30c35f592907bc9a3e9dfdc28e72916c4a7d6511cf4247cbf8a654a21407
|
| 3 |
+
size 313979148
|