Instructions to use nvidia/Flora-TempSeg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nvidia/Flora-TempSeg with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-9B") model = PeftModel.from_pretrained(base_model, "nvidia/Flora-TempSeg") - Notebooks
- Google Colab
- Kaggle
|
Download batch_utils/THIRD_PARTY_NOTICES.md from nvidia/Flora-TempSeg: direct link, hf CLI and curl.
- Browser
- Download file 1.5 kB
-
https://huggingface.co/nvidia/Flora-TempSeg/resolve/refs%2Fpr%2F4/batch_utils/THIRD_PARTY_NOTICES.md
- Command line
-
hf download hf://nvidia/Flora-TempSeg@refs/pr/4/batch_utils/THIRD_PARTY_NOTICES.md
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curl -L -o THIRD_PARTY_NOTICES.md https://huggingface.co/nvidia/Flora-TempSeg/resolve/refs%2Fpr%2F4/batch_utils/THIRD_PARTY_NOTICES.md
1.5 kB
Third-party notices
The inference scripts use the packages below, installed separately by the setup commands. These packages are not bundled in this repository. The requirements match requirements.txt.
The links identify upstream project licenses. Installed distributions and their dependencies retain their own licenses and notices. For version ranges, consult the license files supplied with the installed version.
| Requirement | Upstream license |
|---|---|
torch==2.11.0 |
BSD-3-Clause |
torchvision==0.26.0 |
BSD-3-Clause |
huggingface_hub==1.33.0 |
Apache-2.0 |
transformers==5.8.1 |
Apache-2.0 |
peft==0.18.1 |
Apache-2.0 |
accelerate==1.12.0 |
Apache-2.0 |
safetensors==0.7.0 |
Apache-2.0 |
av==16.0.1 |
BSD-3-Clause |
numpy<3 |
BSD-3-Clause |
Pillow>=11,<13 |
PIL Software License (MIT-CMU) |