Image-to-Text
Transformers
Safetensors
PEFT
English
vision-language
image-captioning
SmolVLM
LoRA
QLoRA
COCO
accelerate
Instructions to use Amirhossein75/VLM-Image-Captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amirhossein75/VLM-Image-Captioning 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="Amirhossein75/VLM-Image-Captioning")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Amirhossein75/VLM-Image-Captioning", dtype="auto") - PEFT
How to use Amirhossein75/VLM-Image-Captioning with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ff08eb72f48f1131c3962858c84500011458e34f0c348f2e3029fd4ebb52019
- Size of remote file:
- 5.78 kB
- SHA256:
- 75f13b031915b2441b461b5dd16d5b4ac5150b295430ff647cb75614a0dce812
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