Model type:
Causal decoder-only - instruct / chat version
Architecture:
Pure-transformer - 1.58bit version
Language(s) (NLP):
Mainly English
License:
TII Falcon License 2.0
Training details
The model has been trained following the training strategies from the recent
1-bit LLM HF blogpost
and
1-bit LLM paper
.
For more details about the training protocol of this model, please refer to the Falcon-3 technical report, section
Compression
.
Usage
Currently to use this model you can either rely on Hugging Face transformers library or
BitNet
library. You can also play with the model using the
falcon-1.58bit playground
(only for the 7B instruct version).
🤗 transformers
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "tiiuae/Falcon3-3B-Instruct-1.58bit"
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
).to("cuda")
# Perform text generation
BitNet
git clone https://github.com/microsoft/BitNet && cd BitNet
pip install -r requirements.txt
python setup_env.py --hf-repo tiiuae/Falcon3-3B-Instruct-1.58bit -q i2_s
python run_inference.py -m models/Falcon3-3B-1.58bit/ggml-model-i2_s.gguf -p "You are a helpful assistant." -cnv
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