From 4756b0f36607ae2baf2fbb40357241167573a869 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 18 Jul 2026 03:18:06 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: tiiuae/Falcon3-10B-Instruct-GGUF Source: Original Platform --- .gitattributes | 44 +++++++++++ Falcon3-10B-Instruct-f16.gguf | 3 + Falcon3-10B-Instruct-q2_k.gguf | 3 + Falcon3-10B-Instruct-q3_k_m.gguf | 3 + Falcon3-10B-Instruct-q4_0.gguf | 3 + Falcon3-10B-Instruct-q4_k_m.gguf | 3 + Falcon3-10B-Instruct-q5_0.gguf | 3 + Falcon3-10B-Instruct-q5_k_m.gguf | 3 + Falcon3-10B-Instruct-q6_k.gguf | 3 + Falcon3-10B-Instruct-q8_0.gguf | 3 + README.md | 122 +++++++++++++++++++++++++++++++ configuration.json | 1 + 12 files changed, 194 insertions(+) create mode 100644 .gitattributes create mode 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+pipeline_tag: text-generation +library_name: transformers +tags: +- falcon3 + +--- + +
+ drawing +
+ +# Falcon3-10B-Instruct-GGUF + + +**Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B parameters. + +**Falcon3-10B-Instruct** achieves state-of-the-art results (at release's time) on reasoning, language understanding, instruction following, code and mathematics tasks. +Falcon3-10B-Instruct supports 4 languages (English, French, Spanish, Portuguese) and a context length of up to 32K. + +This repository contains the GGUFs instruction-tuned 10B Falcon3 model. + +## Model Details +- Architecture + - Transformer-based causal decoder-only architecture + - 40 decoder blocks + - Grouped Query Attention (GQA) for faster inference: 12 query heads and 4 key-value heads + - Wider head dimension: 256 + - High RoPE value to support long context understanding: 1000042 + - Uses SwiGLu and RMSNorm + - 32K context length + - 131K vocab size +- Depth up-scaled from **Falcon3-7B-Base** with 2 Teratokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using 1024 H100 GPU chips +- Posttrained on 1.2 million samples of STEM, conversational, code, safety and function call data +- Supports EN, FR, ES, PT +- Developed by [Technology Innovation Institute](https://www.tii.ae) +- License: TII Falcon-LLM License 2.0 +- Model Release Date: December 2024 +- Quantization: q2_K, q3_K_M, q4_0, q4_K_M, q5_0, q5_K_M, q6_K, q8_0 + + +## Getting started + +### 1. Download GGUF models from hugging face + +First, download the model from Hugging Face. You can use the `huggingface_hub` library or download it manually: + +```bash +pip install huggingface_hub +huggingface-cli download {model_name} +``` + +This will download the model to your current directory. Make sure to replace {model_name} with the actual username and model name from your Hugging Face repository. + +## 2. Install llama.cpp + +You have several options for installing llama.cpp: + +**1. Build from source:** + +This gives you the most flexibility and control. Follow the instructions in the llama.cpp repository to build from source: + +```bash + +git clone https://github.com/ggerganov/llama.cpp +cd llama.cpp +cmake -B build +cmake --build build --config Release +``` + +For more information about how to build llama.cpp from source please refere to llama.cpp documentation on how to build from source: **[llama.cpp build from source](https://github.com/ggerganov/llama.cpp/blob/master/docs/build.md)**. + +**2. Download pre-built binaries:** + +If you prefer a quicker setup, you can download pre-built binaries for your operating system. Check the llama.cpp repository for available binaries. + +**3. Use Docker:** + +For a more contained environment, you can use the official llama.cpp Docker image. Refer to the llama.cpp documentation for instructions on how to use the Docker image. + +For detailed instructions and more information, please check the llama.cpp documentation on docker: **[llama.cpp docker](https://github.com/ggerganov/llama.cpp/blob/master/docs/docker.mdg)**. + +### 3. Start playing with your model + +Run simple text completion +```bash +llama-cli -m {path-to-gguf-model} -p "I believe the meaning of life is" -n 128 +``` + +Run in conversation mode +```bash +llama-cli -m {path-to-gguf-model} -p "You are a helpful assistant" -cnv -co +``` + +## Useful links +- View our [release blogpost](https://huggingface.co/blog/falcon3). +- Feel free to join [our discord server](https://discord.gg/fwXpMyGc) 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} +} +``` \ No newline at end of file diff --git a/configuration.json b/configuration.json new file mode 100644 index 0000000..bbeeda1 --- /dev/null +++ b/configuration.json @@ -0,0 +1 @@ +{"framework": "pytorch", "task": "text-generation", "allow_remote": true} \ No newline at end of file