Initial commit

.gitattributes

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.gitignore

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+.DS_Store
+
+# Android files
+.gradle
+*.iml
+local.properties

LICENSE

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README.md

@@ -0,0 +1,116 @@
+---
+library_name: diffusers
+license: apache-2.0
+license_link: https://huggingface.co/BAAI/URSA-1.7B-FSQ320/blob/main/LICENSE
+pipeline_tag: text-to-video
+base_model:
+- Qwen/Qwen3-1.7B
+---
+
+# URSA-1.7B-FSQ320 Model Card 
+
+## Model Details
+- **Developed by:** BAAI
+- **Model type:** Text-to-Video Generation Model
+- **Model size:** 1.7B
+- **Model precision:** torch.float16 (FP16)
+- **Model resolution:** 512x320
+- **Model family:** [BAAI-Vision-URSA](https://github.com/baaivision/URSA)
+- **Model Tokenizer:** [Cosmos-Tokenize1-DV4x8x8-360p](https://huggingface.co/nvidia/Cosmos-Tokenize1-DV4x8x8-360p)
+- **Model Description:** This is a model that can be used to generate and modify videos based on text prompts.
+
+## Examples
+
+Using the [🤗's Diffusers library](https://github.com/huggingface/diffusers) to run URSA in a simple and efficient manner.
+
+```bash
+pip install diffusers transformers accelerate imageio[ffmpeg]
+pip install git+ssh://[email protected]/baaivision/URSA.git
+```
+
+Running the pipeline:
+
+```python
+import os, torch, numpy
+from diffnext.pipelines import URSAPipeline
+from diffnext.utils import export_to_video
+os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
+
+model_id, height, width = "BAAI/URSA-1.7B-FSQ320", 320, 512
+model_args = {"torch_dtype": torch.float16, "trust_remote_code": True}
+pipe = URSAPipeline.from_pretrained(model_id, **model_args)
+pipe = pipe.to(torch.device("cuda"))
+
+text_prompt = "a lone grizzly bear walks through a misty forest at dawn, sunlight catching its fur."
+negative_prompt = "worst quality, low quality, inconsistent motion, static, still, blurry, jittery, distorted, ugly"
+
+# Text-to-Image
+prompt = text_prompt
+num_frames, num_inference_steps = 1, 25
+image = pipe(**locals()).frames[0]
+image.save("ursa.jpg")
+
+# Image-to-Video
+prompt = f"motion=9.0, {text_prompt}"
+num_frames, num_inference_steps = 49, 50
+video = pipe(**locals()).frames[0]
+export_to_video(video, "ursa_1+48f.mp4", fps=12)
+
+# Text-to-Video
+image, video = None, None
+prompt = f"motion=9.0, {text_prompt}"
+num_frames, num_inference_steps = 49, 50
+video = pipe(**locals()).frames[0]
+export_to_video(video, "ursa_49f.mp4", fps=12)
+
+# Video-to-Video
+prompt = f"motion=5.0, {text_prompt}"
+num_frames, num_inference_steps = 49, 50
+num_cond_frames, cond_noise_scale = 13, 0.1
+for i in range(12):
+    video, start_video = video[-num_cond_frames:], video
+    video = pipe(**locals()).frames[0]
+    video = numpy.concatenate([start_video, video[num_cond_frames:]])
+    export_to_video(video, "ursa_{}f.mp4".format(video.shape[0]), fps=12)
+```
+
+# Uses
+
+## Direct Use 
+The model is intended for research purposes only. Possible research areas and tasks include
+
+- Research on generative models.
+- Applications in educational or creative tools.
+- Generation of artworks and use in design and other artistic processes.
+- Probing and understanding the limitations and biases of generative models.
+- Safe deployment of models which have the potential to generate harmful content.
+
+Excluded uses are described below.
+
+#### Out-of-Scope Use
+The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.
+
+#### Misuse and Malicious Use
+Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
+
+- Mis- and disinformation.
+- Representations of egregious violence and gore.
+- Impersonating individuals without their consent.
+- Sexual content without consent of the people who might see it.
+- Sharing of copyrighted or licensed material in violation of its terms of use.
+- Intentionally promoting or propagating discriminatory content or harmful stereotypes.
+- Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.
+- Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.
+
+## Limitations and Bias
+
+### Limitations
+
+- The autoencoding part of the model is lossy.
+- The model cannot render complex legible text.
+- The model does not achieve perfect photorealism.
+- The fingers, .etc in general may not be generated properly.
+- The model was trained on a subset of the web datasets [LAION-5B](https://laion.ai/blog/laion-5b/) and [COYO-700M](https://github.com/kakaobrain/coyo-dataset), which contains adult, violent and sexual content.
+
+### Bias
+While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.

model_index.json

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+{
+  "_class_name": "URSAPipeline",
+  "tokenizer": [
+    "transformers",
+    "Qwen2TokenizerFast"
+  ],
+  "scheduler": [
+    "__scheduler__",
+    "KineticOptimalScheduler"
+  ],
+  "transformer": [
+    "__transformer__",
+    "URSATransformer3DModel"
+  ],
+  "vae": [
+    "__vae__",
+    "AutoencoderVQCosmos3D"
+  ]
+}

scheduler/__scheduler__.py

@@ -0,0 +1,17 @@
+# Copyright (c) 2024-present, BAAI. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+##############################################################################
+"""Scheduler."""
+
+from diffnext.schedulers.scheduling_dfm import KineticOptimalScheduler  # noqa

scheduler/scheduler_config.json

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+{
+  "_class_name": "KineticOptimalScheduler",
+  "alpha": 1.0,
+  "c": 5,
+  "eps": 1e-5,
+  "shift": 4.0
+}

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+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- endif %}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

transformer/__transformer__.py

@@ -0,0 +1,17 @@
+# Copyright (c) 2024-present, BAAI. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+##############################################################################
+"""Transformer model."""
+
+from diffnext.models.transformers.transformer_ursa import URSATransformer3DModel  # noqa

transformer/config.json

@@ -0,0 +1,13 @@
+{
+  "hidden_size": 2048,
+  "intermediate_size": 6144,
+  "max_window_layers": 28,
+  "num_attention_heads": 16,
+  "num_key_value_heads": 8,
+  "num_hidden_layers": 28,
+  "rope_theta": 1000000,
+  "vocab_size": 215669,
+  "lm_vocab_size": 151669,
+  "lm_head_size": 64000,
+  "bov_token_id": 151652
+}

transformer/diffusion_pytorch_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4a50d661919972cd5c8640ca3c9e5824945d105fb714a0de2f7610a4e7bebb8
+size 3964379808

vae/__vae__.py

@@ -0,0 +1,17 @@
+# Copyright (c) 2024-present, BAAI. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+##############################################################################
+"""VAE model."""
+
+from diffnext.models.autoencoders.autoencoder_vq_cosmos3d import AutoencoderVQCosmos3D  # noqa

vae/config.json

@@ -0,0 +1,22 @@
+{
+  "_class_name": "AutoencoderVQCosmos3D",
+  "_quantizer_name": "FSQuantizer",
+  "in_channels": 3,
+  "latent_channels": 256,
+  "layers_per_block": 2,
+  "norm_num_groups": 1,
+  "out_channels": 3,
+  "sample_size": 1024,
+  "sample_frames": 49,
+  "num_vq_embeddings": 64000,
+  "vq_embed_dim": 6,
+  "patch_size": 2,
+  "temporal_stride": 4,
+  "spatial_stride": 8,
+  "block_out_channels": [
+    128,
+    256,
+    512,
+    512
+  ]
+}

vae/diffusion_pytorch_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:433a1dd689f7f819ef42bf56f87e2b965e0c30a607edfda385fabac6fa56d43c
+size 225275828