Instructions to use circulartext/thestats2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use circulartext/thestats2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="circulartext/thestats2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("circulartext/thestats2") model = AutoModelForSequenceClassification.from_pretrained("circulartext/thestats2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
CHANGED
|
@@ -1 +1,2 @@
|
|
| 1 |
pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 1 |
pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
|
| 2 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:49226c31b9e452f7fe4d8c3d1277cc955250f75068bc23f57cb1ed8405ed0e1e
|
| 3 |
+
size 437959756
|