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Control HarborโHF services via a web interface
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joelniklausย
updated a
Space about 5 hours ago
joelniklausย
published a
Space 6 days ago
Post
1897
Hugging Face MCP Server v0.4.9
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Attach images from hf_fs tool.
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Attach images from hf_fs tool.
Post
1387
Hugging Face MCP Server v0.3.29
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Included "papers" in the new hf_fs tool. Includes listing of trending/daily.
This is a new tool under observation - disable the "Paper Semantic Search" tool for best results.
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Included "papers" in the new hf_fs tool. Includes listing of trending/daily.
This is a new tool under observation - disable the "Paper Semantic Search" tool for best results.
hf://papers/
โโโ README.md
โโโ daily/
โ โโโ latest
โ โโโ YYYY/
โ โโโ MM/
โ โโโ DD/
โโโ trending/
โโโ ARXIV_ID/
โโโ metadata.json
โโโ paper.md
โโโ models/
โโโ datasets/
โโโ spaces/Post
3462
Hugging Face MCP Server v0.3.17
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SEP-2640 "Skills Over MCP" support added (early access)
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SEP-2640 "Skills Over MCP" support added (early access)
- 3 replies
Post
361
Hugging Face MCP Server v0.3.13
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The hf_jobs tool allows mounting of volumes with hf:// URI's and some additional notes about use for data analysis.
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The hf_jobs tool allows mounting of volumes with hf:// URI's and some additional notes about use for data analysis.
Post
2234
Hugging Face MCP Server v0.3.12
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The hub_repo_details tool now enables Dataset inspection (view splits, sample rows).
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The hub_repo_details tool now enables Dataset inspection (view splits, sample rows).
Post
327
Hugging Face MCP Server v0.3.10
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Reverted
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Reverted
mcp bucket in favour of upcoming MCP App integration. Post
1000
Hugging Face MCP Server v0.3.9
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Users with a bucket named
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Users with a bucket named
mcp will get an additional list_files tool that returns the public URL of contained files. This is primarily intended for use with Gradio Spaces that need URLs as inputs.Post
1018
The experimental MCP
hub_query tool now supports Paper Searching and Details as well as Daily Papers. Post
3753
Hugging Face MCP Server v0.3.2
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- Replace model_search and dataset_search with combined hub_repo_search tool.
- Less distracting description for hf_doc_search
- model_search and dataset_search tool calls will still function (plan to remove next release).
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
- Replace model_search and dataset_search with combined hub_repo_search tool.
- Less distracting description for hf_doc_search
- model_search and dataset_search tool calls will still function (plan to remove next release).
- 4 replies
Post
338
Hugging Face MCP Server v0.3.1
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- Streamable HTTP used for Gradio Connectivity
- SSE Transport (as Server) removed
- Proxy Configuration added for launch of sub-agent tools
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- Streamable HTTP used for Gradio Connectivity
- SSE Transport (as Server) removed
- Proxy Configuration added for launch of sub-agent tools
Post
2565
Hugging Face MCP Server v0.2.46
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- Add "discover" to Dynamic Space tool. Recommend deselecting "space_search" if using dynamic spaces.
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- Add "discover" to Dynamic Space tool. Recommend deselecting "space_search" if using dynamic spaces.
Post
3048
Hugging Face MCP Server v0.2.45
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- New! Experimental dynamic_space tool.
- Default Image Generator changed to Qwen-Image-Fast
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- New! Experimental dynamic_space tool.
- Default Image Generator changed to Qwen-Image-Fast
Post
2287
Hugging Face MCP Server v0.2.40
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Improved progressive disclosure and descriptions for Jobs tool.
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Improved progressive disclosure and descriptions for Jobs tool.
Post
381
Hugging Face MCP Server v0.2.35
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$HF_TOKEN is expanded in Jobs Secrets environment variables.
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$HF_TOKEN is expanded in Jobs Secrets environment variables.
anditoย
authored a
paper 10 months ago
Post
371
Hugging Face MCP Server v0.2.33
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Allow discovery of Product Documentation Library via the Search tool.
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Allow discovery of Product Documentation Library via the Search tool.
Post
3348
Finally, our new paper is out! "๐๐ถ๐ป๐ฒ๐ฉ๐ถ๐๐ถ๐ผ๐ป: ๐ข๐ฝ๐ฒ๐ป ๐๐ฎ๐๐ฎ ๐๐ ๐๐น๐น ๐ฌ๐ผ๐ ๐ก๐ฒ๐ฒ๐ฑ"! ๐ฅณ
FineVision: Open Data Is All You Need (2510.17269)
If you've ever trained a VLM, you know this problem: nobody shares their data mixtures. It's a black box, making replicating SOTA work impossible.
We wanted to change that.
FineVision unifies 200 sources into 24 million samples. With 17.3 million images and 9.5 billion answer tokens, it's the largest open resource of its kind.
In the paper, we share how we built it:
๐ finding and cleaning data at scale
๐งน removing excessive duplicates across sources
๐ค decontaminating against 66 public benchmarks
My favorite part is Figure 6 (in the video!). It's our visual diversity analysis. It shows that FineVision isn't just bigger; it's more balanced and conceptually richer than other open datasets.
NVIDIA's Eagle 2 paper highlighted just how critical this visual diversity is, and our results confirm it: models trained on FineVision consistently outperform those trained on any other open dataset on 11 benchmarks!
๐ To celebrate the paper, Iโm also releasing a concatenated and shuffled version of the full dataset! ๐
Itโs ready to stream, so you can start training your own models right away:
from datasets import load_dataset
d = load_dataset("HuggingFaceM4/FineVision_full_shuffled", split="train", streaming=True)
print(next(iter(d)))
A big shoutout to the first authors: Luis Wiedmann and Orr Zohar. They are rockstars!
FineVision: Open Data Is All You Need (2510.17269)
If you've ever trained a VLM, you know this problem: nobody shares their data mixtures. It's a black box, making replicating SOTA work impossible.
We wanted to change that.
FineVision unifies 200 sources into 24 million samples. With 17.3 million images and 9.5 billion answer tokens, it's the largest open resource of its kind.
In the paper, we share how we built it:
๐ finding and cleaning data at scale
๐งน removing excessive duplicates across sources
๐ค decontaminating against 66 public benchmarks
My favorite part is Figure 6 (in the video!). It's our visual diversity analysis. It shows that FineVision isn't just bigger; it's more balanced and conceptually richer than other open datasets.
NVIDIA's Eagle 2 paper highlighted just how critical this visual diversity is, and our results confirm it: models trained on FineVision consistently outperform those trained on any other open dataset on 11 benchmarks!
๐ To celebrate the paper, Iโm also releasing a concatenated and shuffled version of the full dataset! ๐
HuggingFaceM4/FineVision_full_shuffled Itโs ready to stream, so you can start training your own models right away:
from datasets import load_dataset
d = load_dataset("HuggingFaceM4/FineVision_full_shuffled", split="train", streaming=True)
print(next(iter(d)))
A big shoutout to the first authors: Luis Wiedmann and Orr Zohar. They are rockstars!
- 4 replies
Post
280
Hugging Face MCP Server v0.2.31
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- OpenAI Apps SDK Support for Gradio Content Generation spaces
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- OpenAI Apps SDK Support for Gradio Content Generation spaces