Instructions to use Baicai003/tiny-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Baicai003/tiny-t5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Baicai003/tiny-t5")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Baicai003/tiny-t5") model = AutoModel.from_pretrained("Baicai003/tiny-t5") - Notebooks
- Google Colab
- Kaggle
Upload generation_config.json with huggingface_hub
Browse files- generation_config.json +6 -0
generation_config.json
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"eos_token_id": 1,
|
| 4 |
+
"pad_token_id": 0,
|
| 5 |
+
"transformers_version": "4.33.1"
|
| 6 |
+
}
|