Instructions to use foundkim/topic_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use foundkim/topic_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="foundkim/topic_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("foundkim/topic_classifier") model = AutoModelForSequenceClassification.from_pretrained("foundkim/topic_classifier") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin with git-lfs
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 433340589
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9a7107540fe6440dda4c2e3896dc9584de987a1e92d835a4520a71ce6c3c7611
|
| 3 |
size 433340589
|