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Collections including paper arxiv:2411.04905

OpenCoder Model

OpenCoder Models

Running on Zero

26

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OpenCoder 8B Instruct

8B instruct model from OpenCoder family.
Running on Zero

6

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OpenCoder 1.5B Instruct

1.5B instruct model from OpenCoder family.
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Paper • 2411.04905 • Published Nov 7, 2024 • 114
infly/OpenCoder-1.5B-Base

Text Generation • Updated Nov 11, 2024 • 2.92k • 20

Learning-Material

OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Paper • 2411.04905 • Published Nov 7, 2024 • 114

OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Paper • 2411.04905 • Published Nov 7, 2024 • 114

HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems

Paper • 2411.02959 • Published Nov 5, 2024 • 66
"Give Me BF16 or Give Me Death"? Accuracy-Performance Trade-Offs in LLM Quantization

Paper • 2411.02355 • Published Nov 4, 2024 • 47
CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation

Paper • 2410.23090 • Published Oct 30, 2024 • 54
RARe: Retrieval Augmented Retrieval with In-Context Examples

Paper • 2410.20088 • Published Oct 26, 2024 • 5

CLEAR: Character Unlearning in Textual and Visual Modalities

Paper • 2410.18057 • Published Oct 23, 2024 • 200
CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation

Paper • 2410.23090 • Published Oct 30, 2024 • 54
What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective

Paper • 2410.23743 • Published Oct 31, 2024 • 60
"Give Me BF16 or Give Me Death"? Accuracy-Performance Trade-Offs in LLM Quantization

Paper • 2411.02355 • Published Nov 4, 2024 • 47

glaiveai/glaive-coder-7b

Text Generation • Updated Sep 21, 2023 • 1.17k • 54
glaiveai/glaive-code-assistant-v3

Viewer • Updated May 20, 2024 • 950k • 163 • 46
ibm-granite/granite-3b-code-base-128k

Text Generation • Updated Sep 2, 2024 • 189 • 5
Granite Code Models: A Family of Open Foundation Models for Code Intelligence

Paper • 2405.04324 • Published May 7, 2024 • 22

Interesting Papers

These papers are interesting (to me)

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

Paper • 2410.02740 • Published Oct 3, 2024 • 52
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging

Paper • 2410.01215 • Published Oct 2, 2024 • 30
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models

Paper • 2409.17146 • Published Sep 25, 2024 • 106
EuroLLM: Multilingual Language Models for Europe

Paper • 2409.16235 • Published Sep 24, 2024 • 26

LLMs + Persona-Plug = Personalized LLMs

Paper • 2409.11901 • Published Sep 18, 2024 • 32
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

Paper • 2409.12183 • Published Sep 18, 2024 • 37
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems

Paper • 2402.12875 • Published Feb 20, 2024 • 13
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices

Paper • 2410.00531 • Published Oct 1, 2024 • 30

LinFusion: 1 GPU, 1 Minute, 16K Image

Paper • 2409.02097 • Published Sep 3, 2024 • 33
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion

Paper • 2409.11406 • Published Sep 17, 2024 • 26
Diffusion Models Are Real-Time Game Engines

Paper • 2408.14837 • Published Aug 27, 2024 • 123
Segment Anything with Multiple Modalities

Paper • 2408.09085 • Published Aug 17, 2024 • 22

LLM Pruning and Distillation in Practice: The Minitron Approach

Paper • 2408.11796 • Published Aug 21, 2024 • 58
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Paper • 2408.09174 • Published Aug 17, 2024 • 52
To Code, or Not To Code? Exploring Impact of Code in Pre-training

Paper • 2408.10914 • Published Aug 20, 2024 • 42
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications

Paper • 2408.11878 • Published Aug 20, 2024 • 54

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