Image-to-Text
Transformers
Safetensors
English
Chinese
qwen2_5_vl
image-text-to-text
mathematical-reasoning
visual-reasoning
code-generation
qwen2.5-vl
text-generation-inference
Instructions to use gogoduan/MatPlotCode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gogoduan/MatPlotCode with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="gogoduan/MatPlotCode")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("gogoduan/MatPlotCode") model = AutoModelForImageTextToText.from_pretrained("gogoduan/MatPlotCode") - Notebooks
- Google Colab
- Kaggle
Update generation_config.json
Browse files- generation_config.json +1 -2
generation_config.json
CHANGED
|
@@ -1,13 +1,12 @@
|
|
| 1 |
{
|
| 2 |
"attn_implementation": "flash_attention_2",
|
| 3 |
"bos_token_id": 151643,
|
| 4 |
-
"do_sample":
|
| 5 |
"eos_token_id": [
|
| 6 |
151645,
|
| 7 |
151643
|
| 8 |
],
|
| 9 |
"pad_token_id": 151643,
|
| 10 |
"repetition_penalty": 1.05,
|
| 11 |
-
"temperature": 1e-06,
|
| 12 |
"transformers_version": "4.50.0"
|
| 13 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"attn_implementation": "flash_attention_2",
|
| 3 |
"bos_token_id": 151643,
|
| 4 |
+
"do_sample": false,
|
| 5 |
"eos_token_id": [
|
| 6 |
151645,
|
| 7 |
151643
|
| 8 |
],
|
| 9 |
"pad_token_id": 151643,
|
| 10 |
"repetition_penalty": 1.05,
|
|
|
|
| 11 |
"transformers_version": "4.50.0"
|
| 12 |
}
|