Instructions to use griffin/redress-clinical-hallucination-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use griffin/redress-clinical-hallucination-generator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("griffin/redress-clinical-hallucination-generator") model = AutoModelForSeq2SeqLM.from_pretrained("griffin/redress-clinical-hallucination-generator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,5 +1,6 @@
|
|
| 1 |
# redress-clinical-hallucination-generator
|
| 2 |
-
|
|
|
|
| 3 |
|
| 4 |
[Paper Link](https://arxiv.org/abs/2204.10290#:~:text=In%20many%20real%2Dworld%20scenarios,shown%20to%20reduce%20model%20hallucinations.)
|
| 5 |
|
|
|
|
| 1 |
# redress-clinical-hallucination-generator
|
| 2 |
+
|
| 3 |
+
HuggingFace Model Weights for the Clinical Text Hallucination Generator described in EMNLP Findings '22 paper "Learning to Revise References for Faithful Summarization"
|
| 4 |
|
| 5 |
[Paper Link](https://arxiv.org/abs/2204.10290#:~:text=In%20many%20real%2Dworld%20scenarios,shown%20to%20reduce%20model%20hallucinations.)
|
| 6 |
|