| --- |
| pipeline_tag: text-to-video |
| tags: |
| - text-to-video |
| - pytorch |
| - safetensors |
| --- |
| # Elastic Forcing Checkpoints |
|
|
| Generator checkpoints for autoregressive text-to-video generation. Use them with the [Elastic Forcing code](https://huggingface.co/Elastic-forcing/Elastic-forcing-code). |
|
|
| | Model | Training updates | Format | Precision | |
| |---|---:|---|---| |
| | 1.3B | 150 | `checkpoints/1.3B/model.pt` | FP32 | |
| | 14B | 80 | Eight safetensors shards and an index under `checkpoints/14B/` | FP32 | |
|
|
| Inference requires the matching Wan2.1 base-model assets, T5 text encoder, tokenizer, and VAE. The frozen feature encoders are required for training. Use the `generator` weights without EMA. |
|
|
| ## Download |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| folder = snapshot_download( |
| "Elastic-forcing/Elastic-forcing-checkpoint", |
| allow_patterns=["checkpoints/1.3B/*"], # Select checkpoints/14B/* for the 14B model. |
| ) |
| print(folder) |
| ``` |
|
|
| ## Inference |
|
|
| Follow the [1.3B guide](https://huggingface.co/Elastic-forcing/Elastic-forcing-code/blob/main/1.3B/README.md) or [14B guide](https://huggingface.co/Elastic-forcing/Elastic-forcing-code/blob/main/14B/README.md) to prepare the environment and local base-model assets. |
|
|
| For 1.3B, set `CHECKPOINT` to the downloaded `model.pt`. For 14B, combine the safetensors shards into the generator checkpoint expected by the launcher: |
|
|
| ```python |
| import json |
| from pathlib import Path |
| import torch |
| from safetensors.torch import load_file |
| |
| folder = Path("/path/to/checkpoints/14B") |
| index = json.loads((folder / "model.safetensors.index.json").read_text()) |
| state = {} |
| for shard in sorted(set(index["weight_map"].values())): |
| state.update(load_file(str(folder / shard), device="cpu")) |
| torch.save({"generator": state}, "/path/to/local/model.pt") |
| ``` |
|
|
| The conversion preserves FP32 tensor values and needs sufficient host memory and disk space for the approximately 57 GB model and its output file. Set `CHECKPOINT` to the resulting file and run the corresponding inference launcher. |
|
|
| Source-code license notices are provided in the code repository. Base-model assets and datasets follow their respective upstream terms. |
|
|
