SmolVLM: Redefining small and efficient multimodal models
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mfarreย
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21 days ago
anditoย
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21 days ago
mfarreย
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about 1 month ago
anditoย
authored
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about 1 month ago
manuย
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2
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about 2 months ago
Post
2652
Extremely bullish on
@CohereForAI
's Aya Vision (8B & 32B) - new SOTA open-weight VLMs
- 8B wins up to 81% of the time in its class, better than Gemini Flash
- 32B beats Llama 3.2 90B!
- Covers 23 languages, excels in image captioning, VQA & more
- Integrated on transformers from Day 0!
Efficient multimodal models are here to stay!!๐ฅ
Check out their blog! https://huggingface.co./blog/aya-vision
- 8B wins up to 81% of the time in its class, better than Gemini Flash
- 32B beats Llama 3.2 90B!
- Covers 23 languages, excels in image captioning, VQA & more
- Integrated on transformers from Day 0!
Efficient multimodal models are here to stay!!๐ฅ
Check out their blog! https://huggingface.co./blog/aya-vision
anditoย
authored
a
paper
3 months ago
Post
1643
๐๐ป๐๐ฟ๐ผ๐ฑ๐๐ฐ๐ถ๐ป๐ด ๐๐ต๐ฒ ๐๐ผ๐ฟ๐น๐ฑ'๐ ๐๐บ๐ฎ๐น๐น๐ฒ๐๐ ๐๐ถ๐๐ถ๐ผ๐ป ๐น๐ฎ๐ป๐ด๐๐ฎ๐ด๐ฒ ๐บ๐ผ๐ฑ๐ฒ๐น!
Weโre thrilled to share ๐ฆ๐บ๐ผ๐น๐ฉ๐๐ (256M & 500M)โthe smallest Visual Language Models ever built. Think: running on <1GB of GPU memoryโyou can fine-tune it on your laptop and run it on your toaster!
Why Itโs Game-Changing:
- ๐ข๐๐๐ฝ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ ๐๐ฎ๐ฟ๐ด๐ฒ๐ฟ ๐ ๐ผ๐ฑ๐ฒ๐น๐: Even the 256M model surpasses our SOTA 80B-parameter model from just 17 months ago. Over 300x reduction!
๐ ๐ถ๐ด๐ต๐๐ ๐๐ณ๐ณ๐ถ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐: The 256M version delivers 80% of our 2.2B modelโs performance, and the 500M version hits 90%
๐๐ถ๐ด๐ต๐๐ป๐ถ๐ป๐ด-๐๐ฎ๐๐ ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต: SmolVLM integrates with ColiPali for state-of-the-art retrieval speedsโon par with models 10x bigger. That means cheaper, faster indexing and real-world impact.
Whatโs New Under the Hood:
- ๐ก๐ฒ๐ ๐ฉ๐ถ๐๐ถ๐ผ๐ป ๐๐ป๐ฐ๐ผ๐ฑ๐ฒ๐ฟ: Smaller overall size (400M -> 93M), but with higher resolution.
- ๐๐ถ๐ด๐ต๐ฒ๐ฟ ๐ฃ๐ถ๐ ๐ฒ๐น๐/๐ง๐ผ๐ธ๐ฒ๐ป: 4096 vs. 1820โmore efficient image processing.
- ๐ฆ๐บ๐ฎ๐ฟ๐ ๐ง๐ผ๐ธ๐ฒ๐ป๐ถ๐๐ฎ๐๐ถ๐ผ๐ป: Faster training and a performance boost.
Check our blog: https://huggingface.co./blog/smolervlm
The models: HuggingFaceTB/smolvlm-256m-and-500m-6791fafc5bb0ab8acc960fb0
The demo: HuggingFaceTB/SmolVLM-256M-Demo
Weโre thrilled to share ๐ฆ๐บ๐ผ๐น๐ฉ๐๐ (256M & 500M)โthe smallest Visual Language Models ever built. Think: running on <1GB of GPU memoryโyou can fine-tune it on your laptop and run it on your toaster!
Why Itโs Game-Changing:
- ๐ข๐๐๐ฝ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ ๐๐ฎ๐ฟ๐ด๐ฒ๐ฟ ๐ ๐ผ๐ฑ๐ฒ๐น๐: Even the 256M model surpasses our SOTA 80B-parameter model from just 17 months ago. Over 300x reduction!
๐ ๐ถ๐ด๐ต๐๐ ๐๐ณ๐ณ๐ถ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐: The 256M version delivers 80% of our 2.2B modelโs performance, and the 500M version hits 90%
๐๐ถ๐ด๐ต๐๐ป๐ถ๐ป๐ด-๐๐ฎ๐๐ ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต: SmolVLM integrates with ColiPali for state-of-the-art retrieval speedsโon par with models 10x bigger. That means cheaper, faster indexing and real-world impact.
Whatโs New Under the Hood:
- ๐ก๐ฒ๐ ๐ฉ๐ถ๐๐ถ๐ผ๐ป ๐๐ป๐ฐ๐ผ๐ฑ๐ฒ๐ฟ: Smaller overall size (400M -> 93M), but with higher resolution.
- ๐๐ถ๐ด๐ต๐ฒ๐ฟ ๐ฃ๐ถ๐ ๐ฒ๐น๐/๐ง๐ผ๐ธ๐ฒ๐ป: 4096 vs. 1820โmore efficient image processing.
- ๐ฆ๐บ๐ฎ๐ฟ๐ ๐ง๐ผ๐ธ๐ฒ๐ป๐ถ๐๐ฎ๐๐ถ๐ผ๐ป: Faster training and a performance boost.
Check our blog: https://huggingface.co./blog/smolervlm
The models: HuggingFaceTB/smolvlm-256m-and-500m-6791fafc5bb0ab8acc960fb0
The demo: HuggingFaceTB/SmolVLM-256M-Demo
- 1 reply
Post
1971
SmolVLM speeding locally on a laptop thanks to mlx-vlm and
@Gradio ! Try it with two lines:
pip install git+https://github.com/andimarafioti/mlx-vlm.git@stream-generate-fix
python -m mlx_vlm.chat_ui --model mlx-community/SmolVLM-Instruct-8bit
Gotta love the MLX community! Big thanks to @pcuenq and @prince_canuma !
@Gradio ! Try it with two lines:
pip install git+https://github.com/andimarafioti/mlx-vlm.git@stream-generate-fix
python -m mlx_vlm.chat_ui --model mlx-community/SmolVLM-Instruct-8bit
Gotta love the MLX community! Big thanks to @pcuenq and @prince_canuma !
Post
3390
Let's go! We are releasing SmolVLM, a smol 2B VLM built for on-device inference that outperforms all models at similar GPU RAM usage and tokens throughputs.
- SmolVLM generates tokens 7.5 to 16 times faster than Qwen2-VL! ๐คฏ
- Other models at this size crash a laptop, but SmolVLM comfortably generates 17 tokens/sec on a macbook! ๐
- SmolVLM can be fine-tuned on a Google collab! Or process millions of documents with a consumer GPU!
- SmolVLM even outperforms larger models in video benchmarks, despite not even being trained on videos!
Check out more!
Demo: HuggingFaceTB/SmolVLM
Blog: https://huggingface.co./blog/smolvlm
Model: HuggingFaceTB/SmolVLM-Instruct
Fine-tuning script: https://github.com/huggingface/smollm/blob/main/finetuning/Smol_VLM_FT.ipynb
- SmolVLM generates tokens 7.5 to 16 times faster than Qwen2-VL! ๐คฏ
- Other models at this size crash a laptop, but SmolVLM comfortably generates 17 tokens/sec on a macbook! ๐
- SmolVLM can be fine-tuned on a Google collab! Or process millions of documents with a consumer GPU!
- SmolVLM even outperforms larger models in video benchmarks, despite not even being trained on videos!
Check out more!
Demo: HuggingFaceTB/SmolVLM
Blog: https://huggingface.co./blog/smolvlm
Model: HuggingFaceTB/SmolVLM-Instruct
Fine-tuning script: https://github.com/huggingface/smollm/blob/main/finetuning/Smol_VLM_FT.ipynb
manuย
authored
a
paper
7 months ago
Post
1095
Hugging face presents FineVideo ๐ฅ! Unlocking the next generation of Video understanding ๐
๐คฏ3400 hours of annotated Creative Common videos with rich character descriptions, scene splits, mood, and content descriptions per scene as well as QA pairs.
๐ฅ
@mfarre processed over 2M videos of Youtube-CC to make this incredibly powerful selection.
Very psyched to fine-tune idefics on this dataset. โก๏ธ
Explore the videos: HuggingFaceFV/FineVideo-Explorer
๐คฏ3400 hours of annotated Creative Common videos with rich character descriptions, scene splits, mood, and content descriptions per scene as well as QA pairs.
๐ฅ
@mfarre processed over 2M videos of Youtube-CC to make this incredibly powerful selection.
Very psyched to fine-tune idefics on this dataset. โก๏ธ
Explore the videos: HuggingFaceFV/FineVideo-Explorer
anditoย
authored
2
papers
8 months ago
Post
1636
๐ Introducing Hugging Face's Multilingual Speech-to-Speech! ๐ค
๐ฌOur modular, cross-platform pipeline to run GPT4o-like experiences on device can now seamlessly switch languages mid-conversation with an imperceptible 100ms delay.
๐ Building on an amazing early reception with 2600 stars on GitHub ๐
๐ We are expanding the library to support multiple languages
๐ฅ Try it out with a flag: --language fr
๐คฏ Or don't set the flag and let the system detect the language
๐ก What feature should we add next?
๐ฌOur modular, cross-platform pipeline to run GPT4o-like experiences on device can now seamlessly switch languages mid-conversation with an imperceptible 100ms delay.
๐ Building on an amazing early reception with 2600 stars on GitHub ๐
๐ We are expanding the library to support multiple languages
๐ฅ Try it out with a flag: --language fr
๐คฏ Or don't set the flag and let the system detect the language
๐ก What feature should we add next?
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- 1 reply
anditoย
authored
a
paper
8 months ago
manuย
authored
a
paper
10 months ago
manuย
authored
2
papers
about 1 year ago