Image-to-Text
Transformers
Safetensors
phi3_v
text-generation
chart-captioning
multimodal
vision-language-model
custom_code
Instructions to use junyoung-00/Phi-3.5-vision-instruct-ChartCap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junyoung-00/Phi-3.5-vision-instruct-ChartCap 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="junyoung-00/Phi-3.5-vision-instruct-ChartCap", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("junyoung-00/Phi-3.5-vision-instruct-ChartCap", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle