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Falcon H1 0.5B Base

Developed by tiiuae
Falcon-H1 is a decoder-only causal model with a hybrid Transformers + Mamba architecture developed by TII, focusing on English NLP tasks with excellent performance.
Downloads 485
Release Time : 5/1/2025

Model Overview

Falcon-H1 is an efficient hybrid architecture language model that combines the strengths of Transformers and Mamba, suitable for various natural language processing tasks.

Model Features

Hybrid Architecture
Combines the strengths of Transformers and Mamba architectures to improve model efficiency and performance.
Efficient Inference
Supports multiple inference methods, including transformers, vLLM, and a custom llama.cpp fork.
Excellent Performance
Outperforms peer models in multiple benchmarks, especially in mathematical and scientific tasks.

Model Capabilities

Text Generation
Mathematical Reasoning
Scientific QA
Code Generation

Use Cases

General NLP
QA Systems
Used to build knowledge-based question-answering systems for various domains.
Performs excellently in benchmarks like MMLU and BBH
Mathematical Applications
Mathematical Problem Solving
Solves complex mathematical problems, including tasks like GSM8k and MATH lvl5.
Achieves 60.2% accuracy on GSM8k
Code Generation
Programming Assistance
Generates and completes code to help developers improve efficiency.
Achieves 35.98% accuracy on HumanEval
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