PEFT
Safetensors
lora
trl
sft
lfm2.5-vl
satellite-imagery
paired-image
civilian-infrastructure
conflict-disruption
blackline-atlas
Instructions to use ChrisRPL/lfm25-vl-civilian-conflict-reporter-lora-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ChrisRPL/lfm25-vl-civilian-conflict-reporter-lora-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LiquidAI/LFM2.5-VL-450M") model = PeftModel.from_pretrained(base_model, "ChrisRPL/lfm25-vl-civilian-conflict-reporter-lora-v1") - Notebooks
- Google Colab
- Kaggle
File size: 824 Bytes
b0f4d74 | 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 33 34 35 36 37 38 39 40 | {
"image_processor": {
"data_format": "channels_first",
"do_image_splitting": true,
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": true,
"downsample_factor": 2,
"encoder_patch_size": 16,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "Lfm2VlImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"max_image_tokens": 256,
"max_num_patches": 1024,
"max_pixels_tolerance": 2.0,
"max_tiles": 10,
"min_image_tokens": 64,
"min_tiles": 2,
"resample": 2,
"rescale_factor": 0.00392156862745098,
"return_row_col_info": true,
"size": {
"height": 512,
"width": 512
},
"tile_size": 512,
"use_thumbnail": true
},
"processor_class": "Lfm2VlProcessor"
}
|