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AGI, LLMs, Knowledge Graph, Palmyra, Domain Specific LLM

Recent Activity

melisa  updated a model 5 days ago
Writer/colab
wassemgtk  authored a paper about 2 months ago
Expect the Unexpected: FailSafe Long Context QA for Finance
kiranr  authored a paper about 2 months ago
Expect the Unexpected: FailSafe Long Context QA for Finance
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Writer's activity

wassemgtk 
posted an update about 14 hours ago
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795
I’ve been diving into the iRoPE architecture from Llama 4—a game-changer for long-context models! It interleaves local attention (with RoPE) for short contexts and global attention (with inference-time temp scaling) for long-range reasoning, aiming for infinite context. I’m going to try writing iRoPE—who wants to help?

Code: https://github.com/wassemgtk/iRoPE-try/blob/main/iRoPE.ipynb
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melisa 
updated a model 5 days ago
wassemgtk 
posted an update 12 days ago
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2055
For fun, a new project: SuperTokenizer! A BPE tokenizer trained on C4 to beat GPT-4. Byte-level, A100-powered, and open-source. Messing around with tokens!
https://github.com/wassemgtk/SuperTokenizer
  • 1 reply
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melisa 
authored a paper 19 days ago
wassemgtk 
posted an update about 1 month ago
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1873
# GESAL: Real-Time Adaptation for LLMs


We’re excited to unveil **Graph-Enhanced Singular Adaptive Learning (GESAL)**, a framework that lets LLMs like meta-llama/Llama-3.2-1B adapt in real time using user feedback. Check out the code and white paper on GitHub!

🔗 **Code**: [https://github.com/writer/AI-Adaptive-Learning-GESAL](https://github.com/writer/AI-Adaptive-Learning-GESAL)

---

## Why GESAL?

Static LLMs struggle to adapt without heavy retraining. GESAL solves this with:
- **SVF**: Adapts weights via \( W' = U (\Sigma \cdot z) V^T \), using few parameters.
- **Graph Memory**: Stores adaptations in nodes for scalability.
- **RL**: Updates via \( J(z) = \mathbb{E}[\log \pi_z(y|x) r] \) based on feedback.

---

## How It Works

Ask "How many R’s in ‘strawberry’?" If it says "2" and you say "no," GESAL learns to say "3" next time, avoiding repeats.

---

## Try It

Built with Hugging Face’s transformers:
pip install transformers torch numpy
python Adaptive_Learning_(GESAL).py

Needs a Hugging Face token for Llama-3.2-1B.

---

## Results

GESAL hits 95% accuracy after 5 feedbacks vs. LoRA’s 70%. It’s efficient (~0.5M params) and scalable.
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wassemgtk 
authored a paper about 2 months ago
dmytro-writer 
authored 2 papers about 2 months ago
kiranr 
authored a paper about 2 months ago
muayad 
authored a paper about 2 months ago
samjulien 
posted an update 4 months ago
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1527
🔥 RAG in just a few lines of code?!

Try out our Hacker News Listener with new built-in RAG capabilities and Palmyra X 004 from the team at Writer!

This Writer Framework app:

- Scrapes up to 500 HN stories and comments
- Uploads them to a Knowledge Graph
- Enables interactive chat with the content using graph-based RAG
- Provides source attribution with every response

The best part? Setting up RAG is now incredibly simple - just a few lines of code to connect your Knowledge Graph as a tool with Palmyra X 004.

🤗 Space: samjulien/hacker-news-listener
💻 Code: https://github.com/writer/framework-tutorials/tree/main/hacker-news-social-listener
melisa 
posted an update 7 months ago
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3110
🔥 Introducing "Writing in the Margins (WiM)" - better inference pattern for long context LLMs that solves the Lost-in-the-Middle problem 🔥

Paper page: Writing in the Margins: Better Inference Pattern for Long Context Retrieval (2408.14906)

TL;DR
Make your model write "margin notes" as you chunk prefill the KV cache. Then ask it reread all notes before it speaks up.
Works with humans, works with AI 🤖

WiM leverages the chunked prefill of the key-value cache, which concurrently generates query-based extractive summaries at each step of the prefill that are subsequently reintegrated at the end of the computation. We term these intermediate outputs “margins”, drawing inspiration from the practice of making margin notes for improved comprehension of long contexts in human reading. We show that this technique, which adds only minimal additional computation, significantly improves LLMs long context reasoning capabilities.

Think: Every chunk has a chance to be attended to/ be at the end of the context at least once. 🎉

📊 Results:
- An average accuracy boost of 7.5% in multi-hop reasoning tasks like HotpotQA and MultiHop-RAG.
- Even a 30% increase in F1-score for summarisation-like tasks (CWE).

Plus, WiM fits seamlessly into interactive applications (think: progress bar!). It can provide real-time progress updates during data retrieval and integration, making it user-friendly and transparent - a stark contrast to feeding 1mln tokens to an LLMs and waiting 6 min for the first token. 🤯

👩‍💻🧑‍💻 Check it out and contribute to our open-source project here: https://github.com/writer/writing-in-the-margins

🧠 More about chunked prefill: https://docs.vllm.ai/en/latest/models/performance.html#chunked-prefill
  • 2 replies
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axel-writer 
authored a paper 7 months ago
melisa 
authored a paper 7 months ago
wassemgtk 
authored a paper 7 months ago
kiranr 
authored a paper 7 months ago
melisa 
authored 2 papers 7 months ago
samjulien 
posted an update 8 months ago
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1968
🔥 Today, Writer dropped Palmyra-Med-70b and Palmyra-Fin-70b, two new domain-specific models that are setting a new standard for medical and financial model performance.

TL;DR
Palmyra-Med-70b
🔢 8k and 32k versions available
🚀 MMLU performance of ~86%, outperforming other top models
👨‍⚕️ Great for diagnosing, planning treatments, medical research, insurance coding and billing
📃 Open-model license for non-commercial use cases
🤗 Available on Hugging Face: Writer/Palmyra-Med-70B
💾 Live on NVIDIA NIM: https://build.nvidia.com/writer/palmyra-med-70b

Palmyra-Fin-70b
🚀 Passed the CFA Level III exam with a 73% score — the first model to do so
💸 Skilled at complex tasks like investment research, financial analysis, and sentiment analysis
📈 Outperformed other top models on a long-fin-eval test of real-world use cases
📃 Open-model license for non-commercial use cases
🤗 Available on Hugging Face: https://huggingface.co/Writer/Palmyra-Fin-70B-32K
💾 Live on NVIDIA NIM: https://build.nvidia.com/writer/palmyra-fin-70b-32k

Try them out and let us know what you think!
  • 2 replies
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wassemgtk 
authored a paper 9 months ago