Image-Text-to-Text
PEFT
Safetensors
English
vision-language
vlm
lora
unsloth
agriculture
crop-disease
smolvlm
image-to-text
conversational
Instructions to use W4ashabii/SmolVLM256M_CropDisease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use W4ashabii/SmolVLM256M_CropDisease with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolVLM-256M-Instruct") model = PeftModel.from_pretrained(base_model, "W4ashabii/SmolVLM256M_CropDisease") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use W4ashabii/SmolVLM256M_CropDisease with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for W4ashabii/SmolVLM256M_CropDisease to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for W4ashabii/SmolVLM256M_CropDisease to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for W4ashabii/SmolVLM256M_CropDisease to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="W4ashabii/SmolVLM256M_CropDisease", max_seq_length=2048, )
File size: 586 Bytes
877366f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"image_processor": {
"do_convert_rgb": true,
"do_image_splitting": false,
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "Idefics3ImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"max_image_size": {
"longest_edge": 512
},
"resample": 1,
"rescale_factor": 0.00392156862745098,
"size": {
"longest_edge": 512
}
},
"image_seq_len": 64,
"processor_class": "Idefics3Processor"
}
|