Instructions to use lytang/MiniCheck-Flan-T5-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lytang/MiniCheck-Flan-T5-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lytang/MiniCheck-Flan-T5-Large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lytang/MiniCheck-Flan-T5-Large") model = AutoModelForSeq2SeqLM.from_pretrained("lytang/MiniCheck-Flan-T5-Large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -2,6 +2,7 @@
|
|
| 2 |
language:
|
| 3 |
- en
|
| 4 |
pipeline_tag: text-classification
|
|
|
|
| 5 |
---
|
| 6 |
|
| 7 |
# Model Summary
|
|
@@ -107,5 +108,4 @@ result_df.round(1)
|
|
| 107 |
archivePrefix={arXiv},
|
| 108 |
primaryClass={cs.CL}
|
| 109 |
}
|
| 110 |
-
```
|
| 111 |
-
|
|
|
|
| 2 |
language:
|
| 3 |
- en
|
| 4 |
pipeline_tag: text-classification
|
| 5 |
+
license: mit
|
| 6 |
---
|
| 7 |
|
| 8 |
# Model Summary
|
|
|
|
| 108 |
archivePrefix={arXiv},
|
| 109 |
primaryClass={cs.CL}
|
| 110 |
}
|
| 111 |
+
```
|
|
|