Instructions to use zcahjl3/STORY_ERROR_CLASSIFICATION with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zcahjl3/STORY_ERROR_CLASSIFICATION with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zcahjl3/STORY_ERROR_CLASSIFICATION")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zcahjl3/STORY_ERROR_CLASSIFICATION") model = AutoModelForSequenceClassification.from_pretrained("zcahjl3/STORY_ERROR_CLASSIFICATION", device_map="auto") - Notebooks
- Google Colab
- Kaggle
JL commited on
Commit ·
926cd82
1
Parent(s): 0837c55
Training in progress, epoch 5
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 267861677
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0435cda4c3f2abb79ae55074ed39962d493e09337d86469512f76f5ad665369a
|
| 3 |
size 267861677
|
runs/Mar31_14-33-37_f03c26b1da26/events.out.tfevents.1680273281.f03c26b1da26.986.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c099d51ce3c1d291c55d6d3c92718080339c267b86960cfef3888dd241c2a041
|
| 3 |
+
size 7560
|