Image-Text-to-Text
PEFT
Safetensors
Bengali
vision-language-model
visual-question-answering
bengali
bangla
lora
smolvlm2
vqa
conversational
Instructions to use bhaskar1707/smolvlm2-bangla-bayanno-chitrojera-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bhaskar1707/smolvlm2-bangla-bayanno-chitrojera-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolVLM2-2.2B-Instruct") model = PeftModel.from_pretrained(base_model, "bhaskar1707/smolvlm2-bangla-bayanno-chitrojera-lora") - Notebooks
- Google Colab
- Kaggle
Upload BanglaVLM-v2 LoRA adapter, Experiment 2 results, predictions, training artifacts and visualizations
89fb3e4 verified Download visualizations/experiment2_model_comparison.png from bhaskar1707/smolvlm2-bangla-bayanno-chitrojera-lora: direct link, hf CLI and curl.
- Browser
- Download file 42.8 kB
-
https://huggingface.co/bhaskar1707/smolvlm2-bangla-bayanno-chitrojera-lora/resolve/main/visualizations/experiment2_model_comparison.png
- Command line
-
hf download hf://bhaskar1707/smolvlm2-bangla-bayanno-chitrojera-lora/visualizations/experiment2_model_comparison.png
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curl -L -o experiment2_model_comparison.png https://huggingface.co/bhaskar1707/smolvlm2-bangla-bayanno-chitrojera-lora/resolve/main/visualizations/experiment2_model_comparison.png
42.8 kB
