Image-Text-to-Text
PEFT
Safetensors
lora
egocentric-video
proactive-assistant
streaming-video
eccv-2026
wearable-ai
egocentric-vision
conversational
Instructions to use ambient-intelligence-labs/egoproactive-4b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ambient-intelligence-labs/egoproactive-4b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "ambient-intelligence-labs/egoproactive-4b-lora") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-3750/tokenizer.json from ambient-intelligence-labs/egoproactive-4b-lora: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/ambient-intelligence-labs/egoproactive-4b-lora/resolve/main/checkpoint-3750/tokenizer.json
- Command line
-
hf download hf://ambient-intelligence-labs/egoproactive-4b-lora/checkpoint-3750/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ambient-intelligence-labs/egoproactive-4b-lora/resolve/main/checkpoint-3750/tokenizer.json
20 MB
- Xet hash:
- 777bcaa63794fa47b8f53680be9d6d176f1fcbd7ba03cdc6c3bae2b3d76b323f
- Size of remote file:
- 20 MB
- SHA256:
- 06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
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