Visual Document Retrieval
PEFT
Safetensors
vidore
multimodal_embedding
multilingual_embedding
Text-to-Visual Document (T→VD) retrieval
Instructions to use Metric-AI/ColQwenStella-2b-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Metric-AI/ColQwenStella-2b-multilingual with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Metric-AI/ColQwenStella-base-2b") model = PeftModel.from_pretrained(base_model, "Metric-AI/ColQwenStella-2b-multilingual") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from Metric-AI/ColQwenStella-2b-multilingual: direct link, hf CLI and curl.
- Browser
- Download file 2.78 MB
-
https://huggingface.co/Metric-AI/ColQwenStella-2b-multilingual/resolve/main/vocab.json
- Command line
-
hf download hf://Metric-AI/ColQwenStella-2b-multilingual/vocab.json
-
curl -L -o vocab.json https://huggingface.co/Metric-AI/ColQwenStella-2b-multilingual/resolve/main/vocab.json
2.78 MB
File too large to display, you can check the raw version instead.