| unsloth/Wan2.2-TI2V-5B-GGUF | |
| A mirror of QuantStack/Wan2.2-TI2V-5B-GGUF | |
| (https://huggingface.co/QuantStack/Wan2.2-TI2V-5B-GGUF). | |
| Unsloth has not modified the weights: every file here is byte for byte the file of the same name in the source repository (verified on the Hub's LFS sha256). | |
| The weights derive from Wan2.2-TI2V-5B (https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B), | |
| Copyright 2024-2025 The Alibaba Wan Team Authors, licensed under the Apache License, | |
| Version 2.0. LICENSE is the text the Wan team ships at | |
| https://github.com/Wan-Video/Wan2.2/blob/main/LICENSE.txt, verbatim, appendix placeholder | |
| included. Upstream ships no NOTICE file, so there is nothing further to propagate under | |
| Apache-2.0 section 4(d). | |
| Changes relative to Wan-AI/Wan2.2-TI2V-5B (Apache-2.0 section 4(b)), all of them | |
| QuantStack's work and none of them Unsloth's: | |
| * the diffusion transformer was quantised to GGUF at 13 precisions (Q2_K, Q3_K_S, Q3_K_M, | |
| Q4_0, Q4_1, Q4_K_S, Q4_K_M, Q5_0, Q5_1, Q5_K_S, Q5_K_M, Q6_K, Q8_0), which changes the | |
| numerics; | |
| * the VAE was converted from the original Wan2.2_VAE.pth to Wan2.2_VAE.safetensors. | |
| Not an official Alibaba Wan Team or QuantStack product, and not endorsed by either. | |