hanyang-21 commited on
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Add the model card, configuration and tokenizer

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ text_tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: other
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+ license_name: openmdw1.1-license
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+ license_link: https://openmdw.ai/license/1-1/
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+ base_model: nvidia/Cosmos3-Nano
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+ tags:
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+ - world-model
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+ - neural-rendering
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+ - video-generation
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+ - autoregressive
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+ ---
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+
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+ # AgentGarten renderer
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+
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+ The real-time neural renderer of [AgentGarten: Code Worlds for Evolving Agents](https://mirros.ai/blog/worlds-for-evolving-agents).
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+ A code world (a simulator or a game engine) keeps the state and runs the rules; this model turns the depth and surface
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+ normals it exports into the observations an agent sees, block by block.
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+
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+ - Blog: https://mirros.ai/blog/worlds-for-evolving-agents
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+ - Technical report: https://mirros.ai/report/agent-garten.pdf
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+ - Project page: https://mirros-lab.github.io/agent-garten
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+ - Code: https://github.com/MirroS-Lab/AgentGarten
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+
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+ ## What is in this repository
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+
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+ | File | Contents |
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+ | --- | --- |
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+ | `student.safetensors` | The few-step autoregressive generation tower (7.0 B parameters, BF16), distilled with Adversarial Forcing |
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+ | `und.safetensors` | The frozen text tower of Cosmos3-Nano, unchanged |
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+ | `text_tokenizer/` | The Cosmos3-Nano text tokenizer, unchanged |
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+ | `config.yaml`, `manifest.json` | Network configuration and the file list the loader reads |
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+
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+ The model starts from [Cosmos3-Nano](https://huggingface.co/nvidia/Cosmos3-Nano). It was adapted to depth and normal
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+ conditions, trained as a block-causal autoregressive model, and distilled into a four-step student. Video is encoded
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+ and decoded with the [Wan 2.2 VAE](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B), which is not included here.
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+
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+ ## Use
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+
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+ Install the [AgentGarten code](https://github.com/MirroS-Lab/AgentGarten), then:
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+
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+ ```bash
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+ hf download MirroS-Lab/AgentGarten-renderer --local-dir weights/AgentGarten-renderer
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+ hf download Wan-AI/Wan2.2-TI2V-5B Wan2.2_VAE.pth --local-dir weights/Wan2.2-TI2V-5B
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+ ```
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+
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+ ```python
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+ from wm.inference.cosmos3 import inspect_artifact, load_artifact
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+ from wm.inference.serving import prepare_serving
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+ from wm.networks.cosmos3.streaming import Cosmos3Stream, StreamPolicy
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+
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+ artifact = load_artifact(inspect_artifact("weights/AgentGarten-renderer"))
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+ prepare_serving(artifact.student)
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+ stream = Cosmos3Stream(artifact.student, StreamPolicy())
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+ ```
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+
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+ The repository's README shows the streaming loop: each block of four latent frames is denoised in four steps and then
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+ committed to the key-value cache, so the conditions of the next block can depend on what was just generated.
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+
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+ ## License
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+
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+ The weights derive from Cosmos3-Nano and are released under the same
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+ [OpenMDW License Agreement, version 1.1](https://openmdw.ai/license/1-1/). The text tower and the tokenizer are
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+ NVIDIA's files, redistributed unchanged under that license.
config.yaml ADDED
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+ dataloader_val:
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+ dataset:
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+ num_frames: 241
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+ model:
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+ conditioner:
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+ tokenizer_path: text_tokenizer
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+ student:
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+ config:
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+ attention_bias: false
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+ base_fps: 24
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+ enable_fps_modulation: true
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+ first_frame_reference_embedding: true
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+ head_dim: 128
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+ hidden_size: 4096
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+ intermediate_size: 12288
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+ latent_channels: 48
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+ mrope_section:
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+ - 24
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+ - 20
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+ - 20
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+ num_attention_heads: 32
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+ num_hidden_layers: 36
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+ num_key_value_heads: 8
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+ patch_size: 2
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+ rms_norm_eps: 1.0e-06
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+ rope_theta: 5000000.0
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+ special_tokens:
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+ eos_token_id: 151645
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+ temporal_modality_margin: 15000
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+ text_bucket_tokens: 514
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+ timestep_scale: 0.001
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+ vocab_size: 151936
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+ lora: null
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+ "schema": "v2v.raw-dmd-safetensors",
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+ "version": 1,
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+ "iteration": 1270,
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+ "config": "config.yaml",
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+ "student": {
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+ "file": "student.safetensors"
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+ },
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+ "und": {
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+ }
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+ }
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+ "<|object_ref_start|>",
218
+ "<|object_ref_end|>",
219
+ "<|box_start|>",
220
+ "<|box_end|>",
221
+ "<|quad_start|>",
222
+ "<|quad_end|>",
223
+ "<|vision_start|>",
224
+ "<|vision_end|>",
225
+ "<|vision_pad|>",
226
+ "<|image_pad|>",
227
+ "<|video_pad|>"
228
+ ],
229
+ "bos_token": null,
230
+ "clean_up_tokenization_spaces": false,
231
+ "eos_token": "<|im_end|>",
232
+ "errors": "replace",
233
+ "extra_special_tokens": {},
234
+ "model_max_length": 262144,
235
+ "pad_token": "<|endoftext|>",
236
+ "split_special_tokens": false,
237
+ "tokenizer_class": "Qwen2Tokenizer",
238
+ "unk_token": null
239
+ }
text_tokenizer/vocab.json ADDED
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