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README.md

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+---
+license: apache-2.0
+tags:
+  - weather
+  - multimodal
+  - radar
+  - satellite
+  - nowcasting
+  - bagel
+language:
+  - en
+base_model: ByteDance-Seed/BAGEL-7B-MoT
+---
+
+# Omni-Weather
+
+A unified multimodal foundation model for weather understanding, generation, and forecasting, built on [BAGEL-7B-MoT](https://huggingface.co/ByteDance-Seed/BAGEL-7B-MoT).
+
+## Model Description
+
+Omni-Weather fine-tunes the BAGEL 7B Mixture-of-Transformer-Experts model for weather-domain tasks:
+
+- **Weather Understanding (VLM)** - Answering questions about radar and satellite imagery (RadarQA)
+- **Weather Generation (Sat2Rad)** - Generating radar VIL images from satellite IR observations (IR069 + IR107 -> VIL)
+- **Weather Nowcasting** - Predicting future radar frames from historical sequences
+- **Multi-Task Weather Processing** - Downscaling, interpolation, cross-modal translation on SEVIR data
+
+> **Thinking / Chain-of-Thought Reasoning: Coming Soon**
+
+## Files
+
+| File | Size | Description |
+|------|------|-------------|
+| `ema.safetensors` | ~55GB | Fine-tuned model weights (EMA) |
+| `ae.safetensors` | ~320MB | VAE encoder/decoder |
+| `config.json` | - | Model configuration |
+| `llm_config.json` | - | LLM backbone config |
+| `vit_config.json` | - | Vision encoder config |
+| `tokenizer*` | - | Tokenizer files |
+
+## Usage
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="Zhouzone/Omni-Weather",
+    local_dir="models/Omni-Weather",
+    local_dir_use_symlinks=False,
+)
+```
+
+See the [GitHub repository](https://github.com/your-username/omni-weather) for full training and inference instructions.
+
+## Training Details
+
+- **Base Model**: ByteDance-Seed/BAGEL-7B-MoT
+- **Training Data**: SEVIR (sat2rad, multi-task) + RadarQA (understanding)
+- **Training Steps**: 20,000
+- **Hardware**: 8x GPUs with FSDP
+
+## Citation
+
+```bibtex
+@article{omniweather2025,
+  title   = {Omni-Weather: A Unified Multimodal Foundation Model for Weather Understanding and Generation},
+  year    = {2025}
+}
+```
+
+## Acknowledgements
+
+Built upon [BAGEL](https://github.com/ByteDance-Seed/Bagel) by ByteDance-Seed.

ae.safetensors

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+oid sha256:afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38
+size 335304388

config.json

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+{
+  "name": [
+    "BAGEL-7B-MoT"
+  ],
+}

ema.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:32eabc8ace255b5cb7be999612a1ec067f4e7e3d1eb6cf1f84d12cd7bb25290a
+size 58429204680

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "pad_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "repetition_penalty": 1.05,
+  "temperature": 0.7,
+  "top_p": 0.8,
+  "top_k": 20,
+  "transformers_version": "4.37.0"
+}

llm_config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 1000000.0,
+  "sliding_window": 131072,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.43.1",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
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+      "normalized": false,
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+      "special": true
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+      "special": true
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+      "normalized": false,
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|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    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\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    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.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{%- endif %}\n",
+  "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
+}

vit_config.json

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+{
+    "hidden_size": 1152,
+    "image_size": 980,
+    "intermediate_size": 4304,
+    "model_type": "siglip_vision_model",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 27,
+    "patch_size": 14
+}