README.md

---
library_name: transformers
tags:
- bitnet
- falcon3
base_model: tiiuae/Falcon3-10B-Base
license: other 
license_name: falcon-llm-license 
license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html
---


![image/png](https://cdn-uploads.huggingface.co/production/uploads/62441d1d9fdefb55a0b7d12c/c-tosr0FvMlKuKQTojx_6.png)


#  Table of Contents

0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [Training Details](#training-details)
3. [Usage](#usage)
4. [Evaluation](#evaluation)
5. [Citation](#citation)


# TL;DR

# Model Details

## Model Description

- **Developed by:** [https://www.tii.ae](https://www.tii.ae)
- **Model type:** Causal decoder-only
- **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](https://huggingface.co/blog/1_58_llm_extreme_quantization) and [1-bit LLM paper](https://github.com/microsoft/unilm/blob/master/bitnet/The-Era-of-1-bit-LLMs__Training_Tips_Code_FAQ.pdf).
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](https://github.com/microsoft/BitNet) library. You can also play with the model using the [falcon-1.58bit playground](https://huggingface.co/spaces/tiiuae/falcon3-1.58bit-playground) (only for the 7B instruct version).

## 🤗 transformers

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "tiiuae/Falcon3-10B-Base-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/Falcon3-10B-Base-1.58bit -q i2_s
python run_inference.py -m models/Falcon3-10B-1.58bit/ggml-model-i2_s.gguf -p "You are a helpful assistant" -cnv
```

# Evaluation

Coming soon ..

# Citation

Coming soon ..