Falcon3
Collection
Falcon3 family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B parameters.
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Falcon3 family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
This repository contains the Falcon3-Mamba-7B-Instruct. It achieves, compared to similar SSM-based models of the same size, state of art results (at release's time) on reasoning, language understanding, instruction following, code and mathematics tasks. Falcon3-Mamba-7B-Instruct supports a context length up to 32K and was mainly trained on english corpus.
from transformers import AutoTokenizer, AutoModelForCausalLM
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "tiiuae/Falcon3-Mamba-7B-Instruct"
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
prompt = "How many hours in one day?"
messages = [
{"role": "system", "content": "You are a helpful friendly assistant Falcon3 from TII, try to follow instructions as much as possible."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
generated_ids = model.generate(
**model_inputs,
max_new_tokens=1024
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
We report in the following table our internal pipeline benchmarks. For the benchmarks marked by star, we normalize the results with HuggingFace score normalization:
Category | Benchmark | Zamba2-7B-instruct | Jamba-1.5-Mini | Llama-3.1-8B-Instruct | Falcon3-Mamba-7B-Instruct |
---|---|---|---|---|---|
General | MMLU (5-shot) | 30.6 | 68.7 | 55.9 | 65.3 |
MMLU-PRO (5-shot)* | 32.4 | 31.6 | 21.8 | 26.3 | |
IFEval | 69.9 | 65.7 | 78.8 | 71.7 | |
Math | GSM8K (5-shot) | 0 | 74.9 | 19.2 | 65.2 |
MATH Lvl-5 (4-shot) | 13.6 | 6.9 | 10.4 | 27.3 | |
Reasoning | Arc Challenge (25-shot) | 54 | 54.3 | 46.6 | 53.7 |
GPQA (0-shot)* | 10.3 | 11.1 | 6.2 | 7.2 | |
MUSR (0-shot)* | 8.2 | 12.2 | 38.6 | 8.3 | |
BBH (3-shot)* | 33.3 | 35.3 | 43.7 | 25.2 | |
CommonSense Understanding | PIQA (0-shot) | 75.6 | 82.3 | 78.9 | 80.9 |
SciQ (0-shot) | 29.2 | 94.9 | 80.2 | 93.6 | |
OpenbookQA (0-shot) | 45.6 | 45.8 | 46.2 | 47.2 |
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},
author = {Falcon-LLM Team},
month = {December},
year = {2024}
}
Base model
tiiuae/Falcon3-Mamba-7B-Base