Instructions to use ctu-aic/FERNET-C5-csfever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctu-aic/FERNET-C5-csfever with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ctu-aic/FERNET-C5-csfever")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ctu-aic/FERNET-C5-csfever") model = AutoModelForSequenceClassification.from_pretrained("ctu-aic/FERNET-C5-csfever") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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:ee698845fec14e295b1a72c267fbb33a64e705c71e93b7803f88c0cead5dcc3e
|
| 3 |
+
size 651402340
|