Image-to-Text
PEFT
Safetensors
Transformers
English
gemma
gemma-4
gemma-4-e2b
image-captioning
multimodal
lora
abliterated
heretic
Instructions to use codeShare/gemma-4-E2B-it-heretic-image-caption-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use codeShare/gemma-4-E2B-it-heretic-image-caption-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("coder3101/gemma-4-E2B-it-heretic") model = PeftModel.from_pretrained(base_model, "codeShare/gemma-4-E2B-it-heretic-image-caption-adapter") - Transformers
How to use codeShare/gemma-4-E2B-it-heretic-image-caption-adapter 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="codeShare/gemma-4-E2B-it-heretic-image-caption-adapter")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("codeShare/gemma-4-E2B-it-heretic-image-caption-adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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