Instructions to use danielsaggau/scotus_max_linear_frozen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielsaggau/scotus_max_linear_frozen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielsaggau/scotus_max_linear_frozen")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielsaggau/scotus_max_linear_frozen") model = AutoModelForSequenceClassification.from_pretrained("danielsaggau/scotus_max_linear_frozen") - 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:d90cb250e17ece0202e9a718adea958a8befb77c9a50255218ca531de0740b88
|
| 3 |
+
size 167626048
|