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reacted to openfree's post with 🚀 27 days ago
🚀 Gemma3-R1984-27B: Next Generation Agentic AI Platform Model Path: https://huggingface.co/VIDraft/Gemma-3-R1984-27B Space: https://huggingface.co/spaces/VIDraft/Gemma-3-R1984-27B git clone https://huggingface.co/spaces/VIDraft/Gemma-3-R1984-27B 💫 A New Frontier in AI Innovation Gemma3-R1984-27B is a powerful agentic AI platform built on Google's Gemma-3-27B model. It integrates state-of-the-art deep research via web search with multimodal file processing capabilities and handles long contexts up to 8,000 tokens. Designed for local deployment on independent servers using NVIDIA A100 GPUs, it provides high security and prevents data leakage. 🔓 Uncensored and Unrestricted AI Experience Gemma3-R1984-27B comes with all censorship restrictions removed, allowing users to operate any persona without limitations. The model perfectly implements various roles and characters according to users' creative requests, providing unrestricted responses that transcend the boundaries of conventional AI. This unlimited interaction opens infinite possibilities across research, creative work, entertainment, and many other fields. ✨ Key Features 🖼️ Multimodal Processing Images (PNG, JPG, JPEG, GIF, WEBP) Videos (MP4) Documents (PDF, CSV, TXT) and various other file formats 🔍 Deep Research (Web Search) Automatically extracts keywords from user queries Utilizes SERPHouse API to retrieve up to 20 real-time search results Incorporates multiple sources by explicitly citing them in responses 📚 Long Context Handling Capable of processing inputs up to 8,000 tokens Ensures comprehensive analysis of lengthy documents or conversations 🧠 Robust Reasoning Employs extended chain-of-thought reasoning for systematic and accurate answer generation 💼 Use Cases ⚡ Fast-response conversational agents 📊 Document comparison and detailed analysis 👁️ Visual question answering from images and videos 🔬 Complex reasoning and research-based inquiries
reacted to openfree's post with 🔥 27 days ago
🚀 Gemma3-R1984-27B: Next Generation Agentic AI Platform Model Path: https://huggingface.co/VIDraft/Gemma-3-R1984-27B Space: https://huggingface.co/spaces/VIDraft/Gemma-3-R1984-27B git clone https://huggingface.co/spaces/VIDraft/Gemma-3-R1984-27B 💫 A New Frontier in AI Innovation Gemma3-R1984-27B is a powerful agentic AI platform built on Google's Gemma-3-27B model. It integrates state-of-the-art deep research via web search with multimodal file processing capabilities and handles long contexts up to 8,000 tokens. Designed for local deployment on independent servers using NVIDIA A100 GPUs, it provides high security and prevents data leakage. 🔓 Uncensored and Unrestricted AI Experience Gemma3-R1984-27B comes with all censorship restrictions removed, allowing users to operate any persona without limitations. The model perfectly implements various roles and characters according to users' creative requests, providing unrestricted responses that transcend the boundaries of conventional AI. This unlimited interaction opens infinite possibilities across research, creative work, entertainment, and many other fields. ✨ Key Features 🖼️ Multimodal Processing Images (PNG, JPG, JPEG, GIF, WEBP) Videos (MP4) Documents (PDF, CSV, TXT) and various other file formats 🔍 Deep Research (Web Search) Automatically extracts keywords from user queries Utilizes SERPHouse API to retrieve up to 20 real-time search results Incorporates multiple sources by explicitly citing them in responses 📚 Long Context Handling Capable of processing inputs up to 8,000 tokens Ensures comprehensive analysis of lengthy documents or conversations 🧠 Robust Reasoning Employs extended chain-of-thought reasoning for systematic and accurate answer generation 💼 Use Cases ⚡ Fast-response conversational agents 📊 Document comparison and detailed analysis 👁️ Visual question answering from images and videos 🔬 Complex reasoning and research-based inquiries
reacted to sadhaklal's post with 👀 27 days ago
What happens when you combine the Chain of Thought (CoT) reasoning capabilities of LLMs with a heuristic-guided tree search algorithm? In the Tree of Thoughts (ToT) paper, the authors (Yao et al.) have coupled GPT-4 with tree search algorithms to attack a few tasks on which left-to-right CoT struggles. And the results are impressive. For example, on the "Game of 24" task, while GPT-4 with CoT prompting only managed to solve 4% of tasks, ToT achieved a success rate of 74%. I've written a blog post that makes the ToT paper easy to understand and implement by taking you through all the details in a step-by-step manner: https://huggingface.co/blog/sadhaklal/tree-of-thoughts If you are interested in the topics of algorithmic AI, tree search, reasoning, planning, or "System 2" thinking, then you may find this blog post useful.
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reacted to openfree's post with 🚀🔥 27 days ago
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Post
7235
🚀 Gemma3-R1984-27B: Next Generation Agentic AI Platform

Model Path: VIDraft/Gemma-3-R1984-27B
Space: VIDraft/Gemma-3-R1984-27B
git clone VIDraft/Gemma-3-R1984-27B

💫 A New Frontier in AI Innovation
Gemma3-R1984-27B is a powerful agentic AI platform built on Google's Gemma-3-27B model. It integrates state-of-the-art deep research via web search with multimodal file processing capabilities and handles long contexts up to 8,000 tokens. Designed for local deployment on independent servers using NVIDIA A100 GPUs, it provides high security and prevents data leakage.

🔓 Uncensored and Unrestricted AI Experience
Gemma3-R1984-27B comes with all censorship restrictions removed, allowing users to operate any persona without limitations. The model perfectly implements various roles and characters according to users' creative requests, providing unrestricted responses that transcend the boundaries of conventional AI. This unlimited interaction opens infinite possibilities across research, creative work, entertainment, and many other fields.

✨ Key Features
🖼️ Multimodal Processing

Images (PNG, JPG, JPEG, GIF, WEBP)
Videos (MP4)
Documents (PDF, CSV, TXT) and various other file formats

🔍 Deep Research (Web Search)

Automatically extracts keywords from user queries
Utilizes SERPHouse API to retrieve up to 20 real-time search results
Incorporates multiple sources by explicitly citing them in responses

📚 Long Context Handling

Capable of processing inputs up to 8,000 tokens
Ensures comprehensive analysis of lengthy documents or conversations

🧠 Robust Reasoning

Employs extended chain-of-thought reasoning for systematic and accurate answer generation

💼 Use Cases

⚡ Fast-response conversational agents
📊 Document comparison and detailed analysis
👁️ Visual question answering from images and videos
🔬 Complex reasoning and research-based inquiries
·
reacted to sadhaklal's post with 👀 27 days ago
view post
Post
1797
What happens when you combine the Chain of Thought (CoT) reasoning capabilities of LLMs with a heuristic-guided tree search algorithm? In the Tree of Thoughts (ToT) paper, the authors (Yao et al.) have coupled GPT-4 with tree search algorithms to attack a few tasks on which left-to-right CoT struggles. And the results are impressive. For example, on the "Game of 24" task, while GPT-4 with CoT prompting only managed to solve 4% of tasks, ToT achieved a success rate of 74%.

I've written a blog post that makes the ToT paper easy to understand and implement by taking you through all the details in a step-by-step manner: https://huggingface.co/blog/sadhaklal/tree-of-thoughts

If you are interested in the topics of algorithmic AI, tree search, reasoning, planning, or "System 2" thinking, then you may find this blog post useful.