Text Classification
Transformers
PyTorch
English
distilbert
distilbert-base-uncased-finetuned-sst-2-english
Instructions to use rosherd/job_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rosherd/job_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rosherd/job_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rosherd/job_classification") model = AutoModelForSequenceClassification.from_pretrained("rosherd/job_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForSequenceClassification
Browse files- config.json +0 -0
- pytorch_model.bin +2 -2
config.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
pytorch_model.bin
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:bac1d80ece71bd7ae7327dff1bf3640237d87549e1efe014cbce0681c5c31ef0
|
| 3 |
+
size 274379693
|