PEFT
Safetensors
blackline-atlas
lfm2.5-vl
lora
satellite-imagery
sentinel-2
simsat
vision-language-model
civilian-disruption-triage
source-led-evidence
humanitarian
Eval Results (legacy)
Instructions to use ChrisRPL/blackline-atlas-lfm25-vl-sft-hf-corpus-full-v1b-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ChrisRPL/blackline-atlas-lfm25-vl-sft-hf-corpus-full-v1b-adapter 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/blackline-atlas-lfm25-vl-sft-hf-corpus-full-v1b-adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c427b133e7415db8345b357407b04eb6df3f4bc2b3966c5081ea0fc8def2e120
- Size of remote file:
- 17.9 MB
- SHA256:
- 963f65940224243d078241b28364c1b5ad01fa68c7f3a36c3e7fc68693fe8e6a
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