Image-Text-to-Text
PEFT
Safetensors
gemma
gemma4
lora
video-understanding
action-recognition
image-sequence
conversational
Instructions to use bear7011/gemma4-e4b-kinetic3K_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bear7011/gemma4-e4b-kinetic3K_FT with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-e4b-it") model = PeftModel.from_pretrained(base_model, "bear7011/gemma4-e4b-kinetic3K_FT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de1f8f32b71e31ae0e11d17b2d7f73a3a4581ebdc2d7039fe0eaebed12d8d879
- Size of remote file:
- 6.74 kB
- SHA256:
- 2be588ff8c8b6fcd8303c648ab8d3bf2aa58bf5fcdc6821e6579f3a61a41feff
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