Instructions to use keonju/classificationmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keonju/classificationmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keonju/classificationmodel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keonju/classificationmodel") model = AutoModelForSequenceClassification.from_pretrained("keonju/classificationmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 3500
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 497813601
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2663514a87e06667a75a01117ea8d0c0bc21c6ca67a2d6574a0ab51fa1095249
|
| 3 |
size 497813601
|