Text-to-Video
Diffusers
Safetensors
WanPipeline
video-generation
wan2.1
dmd
quantization-aware-training
nvfp4
sparse-attention
Instructions to use memset0/vsqa-preview-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use memset0/vsqa-preview-14b with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("memset0/vsqa-preview-14b", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download model_index.json from memset0/vsqa-preview-14b: direct link, hf CLI and curl.
- Browser
- Download file 400 Bytes
-
https://huggingface.co/memset0/vsqa-preview-14b/resolve/main/model_index.json
- Command line
-
hf download hf://memset0/vsqa-preview-14b/model_index.json
-
curl -L -o model_index.json https://huggingface.co/memset0/vsqa-preview-14b/resolve/main/model_index.json
400 Bytes
| { | |
| "_class_name": "WanPipeline", | |
| "_diffusers_version": "0.33.0.dev0", | |
| "scheduler": [ | |
| "diffusers", | |
| "UniPCMultistepScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "UMT5EncoderModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "T5TokenizerFast" | |
| ], | |
| "transformer": [ | |
| "diffusers", | |
| "WanTransformer3DModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKLWan" | |
| ] | |
| } | |