Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use jacobduncan00/hackMIT-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jacobduncan00/hackMIT-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jacobduncan00/hackMIT-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jacobduncan00/hackMIT-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("jacobduncan00/hackMIT-finetuned-sst2") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2
by librarian-bot - opened
README.md
CHANGED
|
@@ -19,6 +19,7 @@ model_index:
|
|
| 19 |
name: Accuracy
|
| 20 |
type: accuracy
|
| 21 |
value: 0.7970183486238532
|
|
|
|
| 22 |
---
|
| 23 |
|
| 24 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
|
| 19 |
name: Accuracy
|
| 20 |
type: accuracy
|
| 21 |
value: 0.7970183486238532
|
| 22 |
+
base_model: Blaine-Mason/hackMIT-finetuned-sst2
|
| 23 |
---
|
| 24 |
|
| 25 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|