Text Classification
Transformers
ONNX
Safetensors
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use AdamCodd/tinybert-sentiment-amazon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/tinybert-sentiment-amazon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdamCodd/tinybert-sentiment-amazon")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/tinybert-sentiment-amazon") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/tinybert-sentiment-amazon") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -3,7 +3,7 @@ datasets:
|
|
| 3 |
- amazon_polarity
|
| 4 |
base_model: prajjwal1/bert-tiny
|
| 5 |
model-index:
|
| 6 |
-
- name:
|
| 7 |
results:
|
| 8 |
- task:
|
| 9 |
type: text-classification
|
|
|
|
| 3 |
- amazon_polarity
|
| 4 |
base_model: prajjwal1/bert-tiny
|
| 5 |
model-index:
|
| 6 |
+
- name: amazon_polarity
|
| 7 |
results:
|
| 8 |
- task:
|
| 9 |
type: text-classification
|