Add pipeline_tag, library_name, and direct paper link
Browse filesThis PR enhances the model card for `MedVLSynther-3B-RL_10K` by adding key metadata and improving content discoverability:
* **`pipeline_tag: image-text-to-text`**: This categorizes the model for multimodal visual question answering, ensuring it appears under the correct pipeline filter on the Hugging Face Hub.
* **`library_name: transformers`**: Evidence from the `Usage` section and `config.json` confirms compatibility with the 🤗 Transformers library, enabling the automated "how to use" widget on the model page.
* **Direct Paper Link**: A direct link to the paper on the Hugging Face Hub (`https://huggingface.co/papers/2510.25867`) has been added at the top of the model card for easier access to the research.
These updates improve the model's discoverability and user experience on the Hub.
|
@@ -1,15 +1,19 @@
|
|
| 1 |
---
|
| 2 |
-
|
|
|
|
| 3 |
datasets:
|
| 4 |
- MedVLSynther/MedSynVQA-10K
|
| 5 |
language:
|
| 6 |
- en
|
| 7 |
-
|
| 8 |
-
|
|
|
|
| 9 |
---
|
| 10 |
|
| 11 |
# MedVLSynther-3B-RL_10K
|
| 12 |
|
|
|
|
|
|
|
| 13 |
Code: https://github.com/UCSC-VLAA/MedVLSynther
|
| 14 |
Project Page: https://ucsc-vlaa.github.io/MedVLSynther/
|
| 15 |
|
|
@@ -47,7 +51,8 @@ processor = AutoProcessor.from_pretrained(model_name)
|
|
| 47 |
messages_1 = [
|
| 48 |
{
|
| 49 |
"role": "system",
|
| 50 |
-
"content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer
|
|
|
|
| 51 |
},
|
| 52 |
{
|
| 53 |
"role": "user",
|
|
@@ -64,7 +69,8 @@ messages_1 = [
|
|
| 64 |
messages_2 = [
|
| 65 |
{
|
| 66 |
"role": "system",
|
| 67 |
-
"content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer
|
|
|
|
| 68 |
},
|
| 69 |
{
|
| 70 |
"role": "user",
|
|
@@ -72,7 +78,7 @@ messages_2 = [
|
|
| 72 |
{
|
| 73 |
"type": "image",
|
| 74 |
"image": "assets/7bslake.png",
|
| 75 |
-
}
|
| 76 |
{"type": "text", "text": "Does the picture contain kidney? Choices: (A) Yes (B) No"},
|
| 77 |
],
|
| 78 |
}
|
|
|
|
| 1 |
---
|
| 2 |
+
base_model:
|
| 3 |
+
- Qwen/Qwen2.5-VL-3B-Instruct
|
| 4 |
datasets:
|
| 5 |
- MedVLSynther/MedSynVQA-10K
|
| 6 |
language:
|
| 7 |
- en
|
| 8 |
+
license: apache-2.0
|
| 9 |
+
pipeline_tag: image-text-to-text
|
| 10 |
+
library_name: transformers
|
| 11 |
---
|
| 12 |
|
| 13 |
# MedVLSynther-3B-RL_10K
|
| 14 |
|
| 15 |
+
This model is presented in the paper [MedVLSynther: Synthesizing High-Quality Visual Question Answering from Medical Documents with Generator-Verifier LMMs](https://huggingface.co/papers/2510.25867).
|
| 16 |
+
|
| 17 |
Code: https://github.com/UCSC-VLAA/MedVLSynther
|
| 18 |
Project Page: https://ucsc-vlaa.github.io/MedVLSynther/
|
| 19 |
|
|
|
|
| 51 |
messages_1 = [
|
| 52 |
{
|
| 53 |
"role": "system",
|
| 54 |
+
"content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer.
|
| 55 |
+
Write your final answer within <answer> </answer> tags.",
|
| 56 |
},
|
| 57 |
{
|
| 58 |
"role": "user",
|
|
|
|
| 69 |
messages_2 = [
|
| 70 |
{
|
| 71 |
"role": "system",
|
| 72 |
+
"content": "You will solve a problem/request. You should provide your thoughts within <think> </think> tags before providing the answer.
|
| 73 |
+
Write your final answer within <answer> </answer> tags.",
|
| 74 |
},
|
| 75 |
{
|
| 76 |
"role": "user",
|
|
|
|
| 78 |
{
|
| 79 |
"type": "image",
|
| 80 |
"image": "assets/7bslake.png",
|
| 81 |
+
},\
|
| 82 |
{"type": "text", "text": "Does the picture contain kidney? Choices: (A) Yes (B) No"},
|
| 83 |
],
|
| 84 |
}
|