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william marshall

fuzzy-mittenz

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reacted to their post with 🤯 about 16 hours ago

So a cool thing happened, Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package.. I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy https://huggingface.co/IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF -IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF https://huggingface.co/IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF -WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B

updated a model about 17 hours ago

fuzzy-mittenz/gme-Qwen2-VL-2B-Instruct-Q5_K_S-GGUF

updated a collection about 18 hours ago

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fuzzy-mittenz's activity

reacted to their post with 🤯 about 16 hours ago

Post

1316

So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..

I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy

IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF

IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF

-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B

reacted to their post with ❤️ 2 days ago

Post

1316

So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..

I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy

IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF

IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF

-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B

posted an update 3 days ago

Post

1316

So a cool thing happened,
Nomic/GPT4ALL released a "Reasoning/Thinking"(QwQ/o1/o3 type) Model using JavaScript functions to calculate things like the haversine function for distance between two places and so on, it's VERY cool the complex calculative/recursive AI in such a small package..

I was able to adapt their methods to one of my small models "Replicant" 2gb and created a new model with importance matrix Quantization using "THE_KEY" Dataset for better inference in the coding model I pulled from Whiterabbitneo's Qwen2.5 model... I give you Reasoning Rabbit.. enjoy

IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF
-IntelligentEstate/o3-ReasoningRabbit_Q2.5-Cd-7B-IQ4_XS-GGUF

IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF
IntelligentEstate/Replicant_Warder-o3-Q2.5_3B-iQ5_K_S-GGUF

-WhiteRabbitNeo/WhiteRabbitNeo-2.5-Qwen-2.5-Coder-7B

reacted to suayptalha's post with ❤️ 5 days ago

Post

1552

🚀 FastLlama Series is Live!

🦾 Experience faster, lighter, and smarter language models! The new FastLlama makes Meta's LLaMA models work with smaller file sizes, lower system requirements, and higher performance. The model supports 8 languages, including English, German, and Spanish.

🤖 Built on the LLaMA 3.2-1B-Instruct model, fine-tuned with Hugging Face's SmolTalk and MetaMathQA-50k datasets, and powered by LoRA (Low-Rank Adaptation) for groundbreaking mathematical reasoning.

💻 Its compact size makes it versatile for a wide range of applications!
💬 Chat with the model:
🔗 Chat Link: suayptalha/Chat-with-FastLlama
🔗 Model Link: suayptalha/FastLlama-3.2-1B-Instruct

reacted to sayakpaul's post with 🚀 7 days ago

Post

1550

In the past seven days, the Diffusers team has shipped:

1. Two new video models
2. One new image model
3. Two new quantization backends
4. Three new fine-tuning scripts
5. Multiple fixes and library QoL improvements

Coffee on me if someone can guess 1 - 4 correctly.

1 reply

replied to their post 10 days ago

https://x.com/i/spaces/1MnxnDQrkjYGO

reacted to their post with 👀 10 days ago

Post

568

8pm est New Discussion on AI privatization and it's importance for cooperative and confidential development, client services, and family use.

We can also touch on the NEW OPEN SOURCE which will solve MANY of the current problems we face not only with AI but as a society.
8pm
(Sorry upon startup some guy hacked the chat or simply crashed it)
new link for 8pm est
https://x.com/i/spaces/1MnxnDQrkjYGO

1 reply

reacted to csabakecskemeti's post with 👍🔥 10 days ago

Post

4464

The AMD Instinct MI50 (~$110) is surprisingly fast for inference Quantized models.

This runs a Llama 3.1 8B Q8 with Llama.cpp
DevQuasar/Mi50

A little blogpost about the HW
http://devquasar.com/uncategorized/amd-radeon-instinct-mi50-cheap-inference/

posted an update 10 days ago

Post

568

1 reply

reacted to freddyaboulton's post with 😎 10 days ago

Post

1511

Hello Llama 3.2! 🗣️🦙

Build a Siri-like coding assistant that responds to "Hello Llama" in 100 lines of python! All with Gradio, webRTC 😎

freddyaboulton/hey-llama-code-editor

reacted to takarajordan's post with 👀 12 days ago

Post

2199

I'm super excited to release my first open-source text dataset:

WorldScenario 20K is a novel dataset of 20,000 synthetically generated multi-stakeholder scenarios designed to simulate real-world decision-making processes. Each scenario explores a unique environmental, societal, or economic issue.

I used the brand new meta-llama/Llama-3.3-70B-Instruct model to generate this dataset and I put the dataset through some post processing to clean and evaluate the dataset for diversity.

I'd appreciate some feedback and thoughts on my new release! Thanks!

takarajordan/WorldScenario_20K

7 replies

reacted to burtenshaw's post with 👍 21 days ago

Post

2565

For anyone looking to boost their LLM fine-tuning and alignment skills this decemeber. We're running this free and open course called smol course. It’s not big like Li Yin and @mlabonne , it’s just smol.

👷 It focuses on practical use cases, so if you’re working on something, bring it along.

👯‍♀️ It’s peer reviewed and open so you can discuss and get feedback.

🤘 If you’re already a smol pro, feel free to drop a star or issue.

> > Part 1 starts now, and it’s on instruction tuning!

https://github.com/huggingface/smol-course

reacted to openfree's post with 🤗 about 1 month ago

Post

3146

🤗 HuggingFace Trending TOP 300 Board - Featuring AI Rating System
📊 Service Introduction
A comprehensive dashboard that provides at-a-glance access to the real-time TOP 300 trending Spaces, Models, and Datasets on HuggingFace.
Our specially developed AI rating system evaluates the practical value and growth potential of each item.
⭐ Key Features
1. AI Rising Rate

Growth potential evaluation based on creation date and ranking
5-tier star rating system (★★★★★)
Evaluation Criteria:

Recency: Higher relative weights for recently created items
Ranking Impact: Higher relative weights for top rankings
Comprehensive assessment using statistical/analytical models applied to AI

2. AI Popularity Score

Comprehensive evaluation combining objective popularity and Rising Rate
18-tier grading system from AAA+ to B-
Evaluation Elements:

Base Score: Benchmark based on likes, downloads, comments, etc.
Additional Score: Rising Rate applied as a weighted factor
Comprehensive assessment using statistical/analytical models applied to AI

3. Visualization Features

Real-time screenshot capture with caching
Intuitive card-based UI
Responsive grid layout
Pastel gradient design

🎯 Applications

AI/ML Project Trend Analysis
Early Discovery of Promising Models/Datasets
Community Activity Monitoring
Research/Development Direction Reference

💡 Key Advantages

Real-time TOP 300 ranking
AI-based objective evaluation system
Fast loading with caching system
Intuitive and modern UI/UX
Integrated dashboard for 3 categories

🔄 Update Cycle

Real-time data reflection
Manual refresh option
Minimized server load through screenshot caching

🎁 Future Plans

Addition of detailed analysis report feature
Custom filtering options
Time-series trend analysis
Category-specific detailed statistics

🌐 How to Access
openfree/trending-board

#HuggingFace #AI #MachineLearning #TrendingBoard #DataScience #

3 replies

reacted to thomwolf's post with 🧠 about 1 month ago

Post

1639

Interesting long read from @evanmiller-anthropic on having a better founded statistical approach to Language Model Evaluations:
https://www.anthropic.com/research/statistical-approach-to-model-evals

Worth a read if you're into LLM evaluations!

Cc @clefourrier

1 reply

replied to John6666's post about 1 month ago

Yes, thank you very much. I'll be a bit more thoughtful when posting.

reacted to AkimfromParis's post with 👍 about 1 month ago

Post

1453

🇯🇵 The Open Japanese LLM Leaderboard created by LLM-jp 🌸 in partnership with HuggingFace 🤗 was released today!

Blog: https://huggingface.co/blog/leaderboard-japanese
Space: llm-jp/open-japanese-llm-leaderboard

🌍 The leaderboard is available in both Japanese and English
📚 Based on the evaluation tool, llm-jp-eval with more than 20 datasets for Japanese LLMs
📊 The leaderboard showcases all the metrics for NLP experts, plus averages for NLP beginners
💻 For the comfort of users, we chose a horizontal UI, and implemented it in a light and dark theme on Gradio
🔬 The radar chart provides a very interesting visualization of metrics!
🌱 We are using the Japanese research platform, MDX, so please be patient!
⚡ LLMs bigger than +70B will be evaluated soon…

How do you say “GPUs Go Brrr” in Japanese - > GPUがブンブン～! (To pronounce "GPU ga bunbun!") 🔥

4 replies

replied to John6666's post about 1 month ago

I wonder what I'm blacklisted from... french foreign legion?

replied to John6666's post about 1 month ago

The posts are definitely from bots but, it seems, if you can actually get them to engage and provide an email it usually will circle back to some weird website about a 60yo dude and his book. Maybe it was just an angry Frenchman trying to sell me crypto and Italian real estate who really hates Maryland's politics(Something we could have had in common..)
I feel Like I missed out on a lifelong friendship...

reacted to Ameeeee's post with 👀 about 1 month ago

Post

1264

Build a fine-tuning dataset with No Code.

Do you want to build a small dataset for creative writing to fine-tune an Open LLM?
- Find a dataset full of conversations with ChatGPT on the Hugging Face Hub.
- Import it into your Argilla Space.
- Preview the dataset and create a question to label the relevant conversations.
- Label 1000 valid examples of creating writing.
- Use this dataset with Autotrain to fine-tune your model.