Image-Text-to-Text
PEFT
Safetensors
English
lora
sft
trl
smolvlm2
vision-language-model
chartqa
conversational
Instructions to use tuggspeedman-ai/SmolVLM2-2.2B-chartqa-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tuggspeedman-ai/SmolVLM2-2.2B-chartqa-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, "tuggspeedman-ai/SmolVLM2-2.2B-chartqa-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc5c79dfb78cdaf277893eb958726595e297abead992b0bca68e811ee65b8a93
- Size of remote file:
- 5.84 kB
- SHA256:
- 24f0049553976d27c05e2bdebd973d28b28634903852fa1d1a7df7be0bd828f9
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