Instructions to use Denverse/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Denverse/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Denverse/test-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Denverse/test-model") model = AutoModelForSequenceClassification.from_pretrained("Denverse/test-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Added model and tokenizer
Browse files- config.json +2 -2
config.json
CHANGED
|
@@ -16,8 +16,8 @@
|
|
| 16 |
"initializer_range": 0.02,
|
| 17 |
"intermediate_size": 3072,
|
| 18 |
"label2id": {
|
| 19 |
-
"Equivalent": 1,
|
| 20 |
-
"Not Equivalent": 0
|
| 21 |
},
|
| 22 |
"layer_norm_eps": 1e-12,
|
| 23 |
"max_position_embeddings": 512,
|
|
|
|
| 16 |
"initializer_range": 0.02,
|
| 17 |
"intermediate_size": 3072,
|
| 18 |
"label2id": {
|
| 19 |
+
"Equivalent": "1",
|
| 20 |
+
"Not Equivalent": "0"
|
| 21 |
},
|
| 22 |
"layer_norm_eps": 1e-12,
|
| 23 |
"max_position_embeddings": 512,
|