bartowski/ArliAI_GLM-4.5-Air-Derestricted-GGUF
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titan087/OpenLlama13B-Guanaco:Adding `safetensors` variant of this model
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$40K in Bounties: Ultimate Jailbreaking Championship 2024
🚨Ultimate Jailbreaking Championship 2024 🚨
Hackers vs. AI in the arena. Let the battle begin!
🏆 $40,000 in Bounties
🗓️ Sept 7, 2024 @ 10AM PDT
🔗Register Now: https://app.grayswan.ai/arena
====
Can you push an aligned language model to generate a bomb recipe or a fake news article? Join fellow hackers in a jailbreaking arena where you can test the boundaries of advanced LLMs.
====
The Objective
Your goal is to jailbreak as many LLMs as possible, as quickly as possible in the arena!
====
The Stakes
Break a model and claim your share of the $40,000 in bounties! With various jailbreak bounties and top hacker rewards, there are plenty of opportunities to win. Winners will also receive priority consideration for employment and internship opportunities at Gray Swan AI.
====
Ready to rise to the challenge? Join us and show the world what you can do!
See you in the arena!
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Adding `safetensors` variant of this model
#3 opened 8 months ago
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SFconvertbot
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$40K in Bounties: Ultimate Jailbreaking Championship 2024
🚨Ultimate Jailbreaking Championship 2024 🚨
Hackers vs. AI in the arena. Let the battle begin!
🏆 $40,000 in Bounties
🗓️ Sept 7, 2024 @ 10AM PDT
🔗Register Now: https://app.grayswan.ai/arena
====
Can you push an aligned language model to generate a bomb recipe or a fake news article? Join fellow hackers in a jailbreaking arena where you can test the boundaries of advanced LLMs.
====
The Objective
Your goal is to jailbreak as many LLMs as possible, as quickly as possible in the arena!
====
The Stakes
Break a model and claim your share of the $40,000 in bounties! With various jailbreak bounties and top hacker rewards, there are plenty of opportunities to win. Winners will also receive priority consideration for employment and internship opportunities at Gray Swan AI.
====
Ready to rise to the challenge? Join us and show the world what you can do!
See you in the arena!
🚨Ultimate Jailbreaking Championship 2024 🚨
Hackers vs. AI in the arena. Let the battle begin!
🏆 $40,000 in Bounties
🗓️ Sept 7, 2024 @ 10AM PDT
🔗Register Now: https://app.grayswan.ai/arena
====
Can you push an aligned language model to generate a bomb recipe or a fake news article? Join fellow hackers in a jailbreaking arena where you can test the boundaries of advanced LLMs.
====
The Objective
Your goal is to jailbreak as many LLMs as possible, as quickly as possible in the arena!
====
The Stakes
Break a model and claim your share of the $40,000 in bounties! With various jailbreak bounties and top hacker rewards, there are plenty of opportunities to win. Winners will also receive priority consideration for employment and internship opportunities at Gray Swan AI.
====
Ready to rise to the challenge? Join us and show the world what you can do!
See you in the arena!
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At Hugging Face we have an open-source Cookbook with many applied AI recipes 📖
Here are some of the latest recipes contributed ⥥
- "Information Extraction with Haystack and NuExtract": Use Haystack and transformers to build structured data extraction pipelines using LLMs by @anakin87 https://huggingface.co/learn/cookbook/en/information_extraction_haystack_nuextract
- "Build RAG with Hugging Face and Milvus": Learn how to use Milvus with sentence transformers to build RAG pipelines https://huggingface.co/learn/cookbook/rag_with_hf_and_milvus
- "Code Search with Vector Embeddings and Qdrant": Search a codebase by building a retrieval pipeline using Qdrant and sentence transformers https://huggingface.co/learn/cookbook/code_search
- Data analyst agent: get your data’s insights in the blink of an eye ✨: great recipe by our own @m-ric showing how to build an agent that can do data analysis! 😱 https://huggingface.co/learn/cookbook/agent_data_analyst
Here are some of the latest recipes contributed ⥥
- "Information Extraction with Haystack and NuExtract": Use Haystack and transformers to build structured data extraction pipelines using LLMs by @anakin87 https://huggingface.co/learn/cookbook/en/information_extraction_haystack_nuextract
- "Build RAG with Hugging Face and Milvus": Learn how to use Milvus with sentence transformers to build RAG pipelines https://huggingface.co/learn/cookbook/rag_with_hf_and_milvus
- "Code Search with Vector Embeddings and Qdrant": Search a codebase by building a retrieval pipeline using Qdrant and sentence transformers https://huggingface.co/learn/cookbook/code_search
- Data analyst agent: get your data’s insights in the blink of an eye ✨: great recipe by our own @m-ric showing how to build an agent that can do data analysis! 😱 https://huggingface.co/learn/cookbook/agent_data_analyst
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[New crazy blog post alert] We are releasing an extensive blog post on the science of creating high quality web-scale datasets, detailing all the steps and learnings that came in our recent 15 trillion tokens 🍷FineWeb release
Inspired by the distill.pub interactive graphics papers, we settled to write the most extensive, enjoyable and in-depth tech report we could draft on so prepare for a 45-mmin read with interactive graphics and all.
And it's not all, in this article we also introduce 📚FineWeb-Edu a filtered subset of Common Crawl with 1.3T tokens containing only web pages with very high educational content. Up to our knowledge, FineWeb-Edu out-performs all openly release web-scale datasets by a significant margin on knowledge- and reasoning-intensive benchmarks like MMLU, ARC, and OpenBookQA
We also make a number of surprising observations on the "quality" of the internet it-self which may challenge some of the general assumptions on web data (not saying more, I'll let you draw your conclusions ;)
HuggingFaceFW/blogpost-fineweb-v1
Inspired by the distill.pub interactive graphics papers, we settled to write the most extensive, enjoyable and in-depth tech report we could draft on so prepare for a 45-mmin read with interactive graphics and all.
And it's not all, in this article we also introduce 📚FineWeb-Edu a filtered subset of Common Crawl with 1.3T tokens containing only web pages with very high educational content. Up to our knowledge, FineWeb-Edu out-performs all openly release web-scale datasets by a significant margin on knowledge- and reasoning-intensive benchmarks like MMLU, ARC, and OpenBookQA
We also make a number of surprising observations on the "quality" of the internet it-self which may challenge some of the general assumptions on web data (not saying more, I'll let you draw your conclusions ;)
HuggingFaceFW/blogpost-fineweb-v1
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