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
Omar L commited on
Document third-party inference dependencies
Browse filesAdds an installation notice and upstream license references for the inference dependencies. Updates the affected code-manifest documentation hashes.
batch_utils/CODE_MANIFEST.json
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"schema_version": "flora_inference_code_manifest_v1"
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"batch_utils/THIRD_PARTY_NOTICES.md": {
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"schema_version": "flora_inference_code_manifest_v1"
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batch_utils/README.md
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## Setup
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Python 3.12 and a CUDA GPU with 80 GB VRAM are the validated configuration.
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The two models run sequentially. Download/cache space of at least 150 GB is
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recommended for the released FP32 Captioner, base model, and adapter.
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## Setup
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This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use. See [third-party notices](THIRD_PARTY_NOTICES.md).
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Python 3.12 and a CUDA GPU with 80 GB VRAM are the validated configuration.
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The two models run sequentially. Download/cache space of at least 150 GB is
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recommended for the released FP32 Captioner, base model, and adapter.
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batch_utils/THIRD_PARTY_NOTICES.md
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# Third-party notices
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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](requirements.txt).
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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.
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| Requirement | Upstream license |
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| --- | --- |
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| `torch==2.11.0` | [BSD-3-Clause](https://github.com/pytorch/pytorch/blob/v2.11.0/LICENSE) |
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| `torchvision==0.26.0` | [BSD-3-Clause](https://github.com/pytorch/vision/blob/v0.26.0/LICENSE) |
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| `huggingface_hub==1.33.0` | [Apache-2.0](https://github.com/huggingface/huggingface_hub/blob/v1.33.0/LICENSE) |
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| `transformers==5.8.1` | [Apache-2.0](https://github.com/huggingface/transformers/blob/v5.8.1/LICENSE) |
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| `peft==0.18.1` | [Apache-2.0](https://github.com/huggingface/peft/blob/v0.18.1/LICENSE) |
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| `accelerate==1.12.0` | [Apache-2.0](https://github.com/huggingface/accelerate/blob/v1.12.0/LICENSE) |
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| `safetensors==0.7.0` | [Apache-2.0](https://github.com/huggingface/safetensors/blob/v0.7.0/LICENSE) |
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| `av==16.0.1` | [BSD-3-Clause](https://github.com/PyAV-Org/PyAV/blob/v16.0.1/LICENSE.txt) |
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| `numpy<3` | [BSD-3-Clause](https://github.com/numpy/numpy/blob/main/LICENSE.txt) |
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| `Pillow>=11,<13` | [PIL Software License (MIT-CMU)](https://github.com/python-pillow/Pillow/blob/main/LICENSE) |
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