Video-Text-to-Text
Transformers
Safetensors
English
Chinese
mllama
text-generation
multimodal
video
vision-language
sft
custom_code
text-generation-inference
Instructions to use OpenMOSS-Team/moss-video-preview-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMOSS-Team/moss-video-preview-sft with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("OpenMOSS-Team/moss-video-preview-sft", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("OpenMOSS-Team/moss-video-preview-sft", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload moss-video-sft
Browse files
README.md
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We introduce **MOSS-Video-Preview-SFT**, the **offline supervised fine-tuned** checkpoint in the MOSS-Video-Preview series.
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> [!Important]
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> This is an **offline SFT** checkpoint (instruction-tuned). It is **not** the
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This checkpoint is intended for:
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- **Offline video/image understanding** with improved instruction following
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- Serving as a strong starting point for further **
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#### Model Architecture
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## ✅ Intended use
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- **Offline instruction-following** for video/image understanding (recommended default checkpoint for most users).
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- **Finetuning starting point** if you plan to train your own
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## ⚠️ Limitations
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- **Not
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- **Latency/throughput depend on decoding & hardware**: FlashAttention 2 + `bfloat16` on modern GPUs is recommended.
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## 🧩 Requirements
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We introduce **MOSS-Video-Preview-SFT**, the **offline supervised fine-tuned** checkpoint in the MOSS-Video-Preview series.
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> [!Important]
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> This is an **offline SFT** checkpoint (instruction-tuned). It is **not** the Real-Time SFT streaming checkpoint.
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This checkpoint is intended for:
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- **Offline video/image understanding** with improved instruction following
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- Serving as a strong starting point for further **Real-Time SFT** or domain adaptation
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#### Model Architecture
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## ✅ Intended use
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- **Offline instruction-following** for video/image understanding (recommended default checkpoint for most users).
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- **Finetuning starting point** if you plan to train your own Real-Time SFT or domain-specific variant.
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## ⚠️ Limitations
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- **Not Real-Time SFT**: this checkpoint may not expose streaming generation APIs such as `real_time_generate()`.
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- **Latency/throughput depend on decoding & hardware**: FlashAttention 2 + `bfloat16` on modern GPUs is recommended.
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## 🧩 Requirements
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