Falcon3 family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B parameters.
This repository contains the Falcon3-1B-Base. It achieves strong results on reasoning, language understanding, instruction following, code and mathematics tasks.
Falcon3-1B-Base supports 4 languages (English, French, Spanish, Portuguese) and a context length of up to 4K.
It was pruned in terms of depth, width, number of heads, and embedding channels from a larger 3B Falcon model, and was efficiently trained on only 80 GT using a knowledge distillation objective.
⚠️ This is a raw, pretrained model, which should be further finetuned using SFT, RLHF, continued pretraining, etc. for most use cases.
Grouped Query Attention (GQA) for faster inference: 8 query heads and 4 key-value heads
Wider head dimension: 256
High RoPE value to support long context understanding: 1000042
Uses SwiGLU and RMSNorm
4K context length
131K vocab size
Pruned and healed using larger Falcon models (3B and 7B respectively) on only 80 Gigatokens of datasets comprising of web, code, STEM, high quality and multilingual data using 256 H100 GPU chips
Feel free to join our discord server if you have any questions or to interact with our researchers and developers.
Technical Report
Coming soon....
Citation
If the Falcon3 family of models were helpful to your work, feel free to give us a cite.
@misc{Falcon3,
title = {The Falcon 3 Family of Open Models},
url = {https://huggingface.co/blog/falcon3},
author = {Falcon-LLM Team},
month = {December},
year = {2024}
}
