Duplicate from tiiuae/Falcon3-10B-Instruct-GGUF

Co-authored-by: Puneesh Khanna <puneeshkhanna@users.noreply.huggingface.co>

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README.md

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+
+---
+language:
+- en
+- fr
+- es
+- pt
+base_model:
+- tiiuae/Falcon3-10B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- falcon3
+
+---
+
+<div align="center">
+    <img src="https://huggingface.co/datasets/tiiuae/documentation-images/resolve/main/general/falco3-logo.png" alt="drawing" width="500"/>
+</div>
+
+# 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}
+}
+```