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IlyasMoutawwakil
updated
a
Space
13 days ago
jeffboudier
posted
an
update
about 1 month ago
Post
972
New - add your bluesky account to your HF profile:
https://huggingface.co./settings/profile
Is the grass greener, the sky bluer? Will try and figure it out at https://bsky.app/profile/jeffboudier.bsky.social
By the way, HF people starter pack https://bsky.app/starter-pack/huggingface.bsky.social/3laz5x7naiz22
https://huggingface.co./settings/profile
Is the grass greener, the sky bluer? Will try and figure it out at https://bsky.app/profile/jeffboudier.bsky.social
By the way, HF people starter pack https://bsky.app/starter-pack/huggingface.bsky.social/3laz5x7naiz22
jeffboudier
posted
an
update
2 months ago
Post
1072
This week in Inference Endpoints - thx
@erikkaum
for the update!
👀 https://huggingface.co./blog/erikkaum/endpoints-changelog
👀 https://huggingface.co./blog/erikkaum/endpoints-changelog
- 1 reply
jeffboudier
posted
an
update
3 months ago
Post
450
Inference Endpoints got a bunch of cool updates yesterday, this is my top 3
jeffboudier
posted
an
update
3 months ago
Post
4032
Pro Tip - if you're a Firefox user, you can set up Hugging Chat as integrated AI Assistant, with contextual links to summarize or simplify any text - handy!
In this short video I show how to set it up
In this short video I show how to set it up
- 2 replies
derek-thomas
posted
an
update
4 months ago
Post
2126
Here is an AI Puzzle!
When you solve it just use a 😎 emoji.
NO SPOILERS
A similar puzzle might have each picture that has a hidden meaning of summer, winter, fall, spring, and the answer would be seasons.
Its a little dated now (almost a year), so bottom right might be tough.
Thanks to @johko for the encouragement to post!
When you solve it just use a 😎 emoji.
NO SPOILERS
A similar puzzle might have each picture that has a hidden meaning of summer, winter, fall, spring, and the answer would be seasons.
Its a little dated now (almost a year), so bottom right might be tough.
Thanks to @johko for the encouragement to post!
IlyasMoutawwakil
updated
a
Space
6 months ago
IlyasMoutawwakil
updated
2
models
6 months ago
IlyasMoutawwakil
posted
an
update
6 months ago
Post
3993
Last week, Intel's new Xeon CPUs, Sapphire Rapids (SPR), landed on Inference Endpoints and I think they got the potential to reduce the cost of your RAG pipelines 💸
Why ? Because they come with Intel® AMX support, which is a set of instructions that support and accelerate BF16 and INT8 matrix multiplications on CPU ⚡
I went ahead and built a Space to showcase how to efficiently deploy embedding models on SPR for both Retrieving and Ranking documents, with Haystack compatible components: https://huggingface.co./spaces/optimum-intel/haystack-e2e
Here's how it works:
- Document Store: A FAISS document store containing the seven-wonders dataset, embedded, indexed and stored on the Space's persistent storage to avoid unnecessary re-computation of embeddings.
- Retriever: It embeds the query at runtime and retrieves from the dataset N documents that are most semantically similar to the query's embedding.
We use the small variant of the BGE family here because we want a model that's fast to run on the entire dataset and has a small embedding space for fast similarity search. Specifically we use an INT8 quantized bge-small-en-v1.5, deployed on an Intel Sapphire Rapids CPU instance.
- Ranker: It re-embeds the retrieved documents at runtime and re-ranks them based on semantic similarity to the query's embedding. We use the large variant of the BGE family here because it's optimized for accuracy allowing us to filter the most relevant k documents that we'll use in the LLM prompt. Specifically we use an INT8 quantized bge-large-en-v1.5, deployed on an Intel Sapphire Rapids CPU instance.
Space: https://huggingface.co./spaces/optimum-intel/haystack-e2e
Retriever IE: optimum-intel/fastrag-retriever
Ranker IE: optimum-intel/fastrag-ranker
Why ? Because they come with Intel® AMX support, which is a set of instructions that support and accelerate BF16 and INT8 matrix multiplications on CPU ⚡
I went ahead and built a Space to showcase how to efficiently deploy embedding models on SPR for both Retrieving and Ranking documents, with Haystack compatible components: https://huggingface.co./spaces/optimum-intel/haystack-e2e
Here's how it works:
- Document Store: A FAISS document store containing the seven-wonders dataset, embedded, indexed and stored on the Space's persistent storage to avoid unnecessary re-computation of embeddings.
- Retriever: It embeds the query at runtime and retrieves from the dataset N documents that are most semantically similar to the query's embedding.
We use the small variant of the BGE family here because we want a model that's fast to run on the entire dataset and has a small embedding space for fast similarity search. Specifically we use an INT8 quantized bge-small-en-v1.5, deployed on an Intel Sapphire Rapids CPU instance.
- Ranker: It re-embeds the retrieved documents at runtime and re-ranks them based on semantic similarity to the query's embedding. We use the large variant of the BGE family here because it's optimized for accuracy allowing us to filter the most relevant k documents that we'll use in the LLM prompt. Specifically we use an INT8 quantized bge-large-en-v1.5, deployed on an Intel Sapphire Rapids CPU instance.
Space: https://huggingface.co./spaces/optimum-intel/haystack-e2e
Retriever IE: optimum-intel/fastrag-retriever
Ranker IE: optimum-intel/fastrag-ranker
IlyasMoutawwakil
updated
a
model
7 months ago
jeffboudier
posted
an
update
8 months ago
Post
1686
TGI v2.0.2 is out!
- New models (idefics2, phi3)
- Cleaner VLM support in the openai layer
- Upgraded to pytorch 2.3.0
https://github.com/huggingface/text-generation-inference/releases/tag/v2.0.2
Kudos @Narsil @olivierdehaene @drbh and so many contributors!
- New models (idefics2, phi3)
- Cleaner VLM support in the openai layer
- Upgraded to pytorch 2.3.0
https://github.com/huggingface/text-generation-inference/releases/tag/v2.0.2
Kudos @Narsil @olivierdehaene @drbh and so many contributors!
jeffboudier
posted
an
update
9 months ago
Post
1871
These 15 open models are available for serverless inference on Cloudflare Workers AI, powered by GPUs distributed in 150 datacenters globally - 👏
@rita3ko
@mchenco
@jtkipp
@nkothariCF
@philschmid
Cloudflare/hf-curated-models-available-on-workers-ai-66036e7ad5064318b3e45db6
Cloudflare/hf-curated-models-available-on-workers-ai-66036e7ad5064318b3e45db6
derek-thomas
posted
an
update
10 months ago
Post
Defending LLMs against Jailbreaking Attacks via Backtranslation (2402.16459)
**Defending LLMs against Jailbreaking Attacks via Backtranslation**
I really love this! Its a really innovative way to get robust defense against jailbreaking. Its not cheap, 2-3 calls per user request. But for some use-cases it can be worth it!
**Defending LLMs against Jailbreaking Attacks via Backtranslation**
I really love this! Its a really innovative way to get robust defense against jailbreaking. Its not cheap, 2-3 calls per user request. But for some use-cases it can be worth it!
derek-thomas
authored
a
paper
about 1 year ago
echarlaix
authored
a
paper
over 1 year ago