Instructions to use VAST-AI/EdenLive-14B-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VAST-AI/EdenLive-14B-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("VAST-AI/EdenLive-14B-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Download transformer/config.json from VAST-AI/EdenLive-14B-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 499 Bytes
-
https://huggingface.co/VAST-AI/EdenLive-14B-Diffusers/resolve/main/transformer/config.json
- Command line
-
hf download hf://VAST-AI/EdenLive-14B-Diffusers/transformer/config.json
-
curl -L -o config.json https://huggingface.co/VAST-AI/EdenLive-14B-Diffusers/resolve/main/transformer/config.json
499 Bytes
| { | |
| "_class_name": "EdenLiveTransformer3DModel", | |
| "_diffusers_version": "0.41.0.dev0", | |
| "added_kv_proj_dim": 5120, | |
| "attention_head_dim": 128, | |
| "condition_rmsnorm": true, | |
| "eps": 1e-06, | |
| "ffn_dim": 13824, | |
| "freq_dim": 256, | |
| "image_dim": 1280, | |
| "in_channels": 36, | |
| "num_attention_heads": 40, | |
| "num_layers": 40, | |
| "out_channels": 16, | |
| "patch_size": [ | |
| 1, | |
| 2, | |
| 2 | |
| ], | |
| "proxy_channels": 1024, | |
| "qk_norm": "rms_norm_across_heads", | |
| "rope_max_seq_len": 1024, | |
| "text_dim": 4096 | |
| } | |