Fixing Gradient Accumulation
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41
Arthur Zucker
ArthurZ
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Reacted to
davidberenstein1957's
post
with π
6 days ago
For anyone who struggles with NER or information extraction with LLM.
We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. @argilla
Video: https://youtu.be/JvLpaYgNd84?feature=shared
Notebooks and slides included to try it yourself π
Reacted to
LukeNeumann's
post
with π€―
6 days ago
Nine years ago, I uploaded the first 8K resolution video to YouTube and I've been stockpiling 8K footage ever since: https://www.youtube.com/watch?v=sLprVF6d7Ug&t
Should @Overlaiapp release the first open-source 8K video dataset?
Could anyone even fine tune a model with this?π
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ArthurZ's activity
Reacted to
Xenova's
post with π₯
6 days ago
Post
4203
Have you tried out π€ Transformers.js v3? Here are the new features:
β‘ WebGPU support (up to 100x faster than WASM)
π’ New quantization formats (dtypes)
π 120 supported architectures in total
π 25 new example projects and templates
π€ Over 1200 pre-converted models
π Node.js (ESM + CJS), Deno, and Bun compatibility
π‘ A new home on GitHub and NPM
Get started with
Learn more in our blog post: https://huggingface.co/blog/transformersjs-v3
β‘ WebGPU support (up to 100x faster than WASM)
π’ New quantization formats (dtypes)
π 120 supported architectures in total
π 25 new example projects and templates
π€ Over 1200 pre-converted models
π Node.js (ESM + CJS), Deno, and Bun compatibility
π‘ A new home on GitHub and NPM
Get started with
npm i @huggingface/transformers.Learn more in our blog post: https://huggingface.co/blog/transformersjs-v3
- 3 replies
Reacted to
davidberenstein1957's
post with π
6 days ago
Post
1873
For anyone who struggles with NER or information extraction with LLM.
We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. @argilla
Video: https://youtu.be/JvLpaYgNd84?feature=shared
Notebooks and slides included to try it yourself π
We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. @argilla
Video: https://youtu.be/JvLpaYgNd84?feature=shared
Notebooks and slides included to try it yourself π
Reacted to
LukeNeumann's
post with π€―
6 days ago
Post
1190
Nine years ago, I uploaded the first 8K resolution video to YouTube and I've been stockpiling 8K footage ever since: https://www.youtube.com/watch?v=sLprVF6d7Ug&t
Should @Overlaiapp release the first open-source 8K video dataset?
Could anyone even fine tune a model with this?π
Should @Overlaiapp release the first open-source 8K video dataset?
Could anyone even fine tune a model with this?π
- 6 replies
Reacted to
their
post with β€οΈ
6 days ago
Post
2248
Native tensor parallel has landed in transformers!!! https://github.com/huggingface/transformers/pull/34184 thanks a lot to the torch team for their support!
Contributions are welcome to support more models! π₯
Contributions are welcome to support more models! π₯
Reacted to
AkimfromParis's
post with β€οΈπ
6 days ago
Post
1384
π―π΅ The Open Japanese LLM Leaderboard created by LLM-jp πΈ in partnership with HuggingFace π€ was released today!
Blog: https://huggingface.co/blog/leaderboard-japanese
Space: llm-jp/open-japanese-llm-leaderboard
π The leaderboard is available in both Japanese and English
π Based on the evaluation tool, llm-jp-eval with more than 20 datasets for Japanese LLMs
π The leaderboard showcases all the metrics for NLP experts, plus averages for NLP beginners
π» For the comfort of users, we chose a horizontal UI, and implemented it in a light and dark theme on Gradio
π¬ The radar chart provides a very interesting visualization of metrics!
π± We are using the Japanese research platform, MDX, so please be patient!
β‘ LLMs bigger than +70B will be evaluated soonβ¦
How do you say βGPUs Go Brrrβ in Japanese - > GPUγγγ³γγ³ο½! (To pronounce "GPU ga bunbun!") π₯
Blog: https://huggingface.co/blog/leaderboard-japanese
Space: llm-jp/open-japanese-llm-leaderboard
π The leaderboard is available in both Japanese and English
π Based on the evaluation tool, llm-jp-eval with more than 20 datasets for Japanese LLMs
π The leaderboard showcases all the metrics for NLP experts, plus averages for NLP beginners
π» For the comfort of users, we chose a horizontal UI, and implemented it in a light and dark theme on Gradio
π¬ The radar chart provides a very interesting visualization of metrics!
π± We are using the Japanese research platform, MDX, so please be patient!
β‘ LLMs bigger than +70B will be evaluated soonβ¦
How do you say βGPUs Go Brrrβ in Japanese - > GPUγγγ³γγ³ο½! (To pronounce "GPU ga bunbun!") π₯
- 4 replies
Reacted to
monsoon-nlp's
post with π
6 days ago
Post
1364
Great to see Tatta Bio release an embeddings version of their DNA/protein language model π§¬:
tattabio/gLM2_650M_embed
Reacted to
AdinaY's
post with π
6 days ago
Post
993
Build a collection for the trending demos recently released by the Chinese community π From Qwen2.5 Turbo to FishAgent, see what these models can really do π₯
zh-ai-community/trending-demo-673b6ca2416a3b3c9d3bf8f1
zh-ai-community/trending-demo-673b6ca2416a3b3c9d3bf8f1
Reacted to
jsulz's
post with π
6 days ago
Post
1974
In August, the XetHub team joined Hugging Face
- https://huggingface.co/blog/xethub-joins-hf - and weβve been rolling up our sleeves to bring the best of both worlds together. We started with a deep dive into the current state of files stored with Git LFS on the Hub.
Getting this information was no small feat. We had to:
* Analyze a complete database dump of all repositories and files stored in Git LFS across Hugging Face.
* Parse through metadata on file sizes and types to accurately map the storage breakdown across Spaces, Models, and Datasets.
You can read more about the findings (with some jaw-dropping stats + charts) here https://www.linkedin.com/feed/update/urn:li:activity:7244486280351285248
- https://huggingface.co/blog/xethub-joins-hf - and weβve been rolling up our sleeves to bring the best of both worlds together. We started with a deep dive into the current state of files stored with Git LFS on the Hub.
Getting this information was no small feat. We had to:
* Analyze a complete database dump of all repositories and files stored in Git LFS across Hugging Face.
* Parse through metadata on file sizes and types to accurately map the storage breakdown across Spaces, Models, and Datasets.
You can read more about the findings (with some jaw-dropping stats + charts) here https://www.linkedin.com/feed/update/urn:li:activity:7244486280351285248
Reacted to
jsulz's
post with π§
6 days ago
Post
2836
When the XetHub crew joined Hugging Face this fall,
@erinys
and I started brainstorming how to share our work to replace Git LFS on the Hub. Uploading and downloading large models and datasets takes precious time. Thatβs where our chunk-based approach comes in.
Instead of versioning files (like Git and Git LFS), we version variable-sized chunks of data. For the Hugging Face community, this means:
β© Only upload the chunks that changed.
π Download just the updates, not the whole file.
π§ We store your file as deduplicated chunks
In our benchmarks, we found that using CDC to store iterative model and dataset version led to transfer speedups of ~2x, but this isnβt just a performance boost. Itβs a rethinking of how we manage models and datasets on the Hub.
We're planning on our new storage backend to the Hub in early 2025 - check out our blog to dive deeper, and let us know: how could this improve your workflows?
https://huggingface.co/blog/from-files-to-chunks
Instead of versioning files (like Git and Git LFS), we version variable-sized chunks of data. For the Hugging Face community, this means:
β© Only upload the chunks that changed.
π Download just the updates, not the whole file.
π§ We store your file as deduplicated chunks
In our benchmarks, we found that using CDC to store iterative model and dataset version led to transfer speedups of ~2x, but this isnβt just a performance boost. Itβs a rethinking of how we manage models and datasets on the Hub.
We're planning on our new storage backend to the Hub in early 2025 - check out our blog to dive deeper, and let us know: how could this improve your workflows?
https://huggingface.co/blog/from-files-to-chunks
Upload transformers version
5
#3 opened 8 days ago
by
ArthurZ
ArthurZ
updated
a
model
8 days ago
posted
an
update
8 days ago
Post
2248
Native tensor parallel has landed in transformers!!! https://github.com/huggingface/transformers/pull/34184 thanks a lot to the torch team for their support!
Contributions are welcome to support more models! π₯
Contributions are welcome to support more models! π₯
liked
a
model
8 days ago
Upload Meta-Llama-3-8B-Instruct, seqlen = 512, python, w_ compile.png
1
#392 opened 12 days ago
by
kwen2501
kwen2501
liked
a
model
22 days ago
liked
a
dataset
about 1 month ago
liked
a
model
about 1 month ago
Update model weight
8
#13 opened about 1 month ago
by
nguyen-brat
nguyen-brat
liked
a
model
about 1 month ago