update llama4 tutorial

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djw 2025-04-09 09:34:04 +00:00
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<h2 id="Updates">🔥 Updates</h2> <h2 id="Updates">🔥 Updates</h2>
* **Apr 9, 2025**: Experimental support for LLaMA 4 models ([Tutorial](./en/llama4.md)).
* **Apr 2, 2025**: Support Multi-concurrency. ([Tutorial](./en/balance-serve.md)). * **Apr 2, 2025**: Support Multi-concurrency. ([Tutorial](./en/balance-serve.md)).
* **Mar 27, 2025**: Support Multi-concurrency. * **Mar 27, 2025**: Support Multi-concurrency.
* **Mar 15, 2025**: Support ROCm on AMD GPU ([Tutorial](./en/ROCm.md)). * **Mar 15, 2025**: Support ROCm on AMD GPU ([Tutorial](./en/ROCm.md)).

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# 🦙 Tutorial: LLaMA 4 Multi-Concurrency Support with KTransformers (Balance Serve Backend)
## 📌 Overview
We are pleased to announce that **KTransformers** now provides **experimental support for LLaMA 4 models** through the powerful `balance_serve` backend introduced in **v0.2.4**. This update is available under the dedicated development branch: [`support-llama4`](https://github.com/kvcache-ai/ktransformers/tree/support-llama4), specifically targeting the newly released **Meta LLaMA 4** model architecture.
⚠️ This support is currently **not available on the main branch** due to dependencies on newer versions of `transformers`, and **compatibility limitations with inference of currently supported models**. Work is underway to integrate this into the mainline once broader stability and compatibility are validated.
💡 **If you already have an environment based on the main branch**, it is **strongly recommended to create a new environment** to avoid potential dependency conflicts.
------
## 🔗 Model & Resource Links
- 🔥 Official LLaMA 4 Release: https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct
(Note: LLaMA 4 models are served through the Meta repository. Make sure to **agree to terms** before downloading.)
- 🧠 GGUF Format (quantized models):
- https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-GGUF
------
## 🧪 Demo
https://github.com/user-attachments/assets/449706f1-784b-4931-b2ba-07687c1aca54
------
## ⚙️ Usage Instructions
### 1. Clone `support-llama4` Branch
```bash
git clone https://github.com/kvcache-ai/ktransformers.git
cd ktransformers
git checkout support-llama4
git submodule update --init --recursive
```
### 2. Set Up Environment
```bash
# Download Miniconda
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
# Create environment
conda create --name ktransformers python=3.11
conda activate ktransformers
# Install required libraries
conda install -c conda-forge libstdcxx-ng
# Verify GLIBCXX version (should include 3.4.32)
strings ~/anaconda3/envs/ktransformers/lib/libstdc++.so.6 | grep GLIBCXX
sudo apt install libtbb-dev libssl-dev libcurl4-openssl-dev libaio1 libaio-dev libfmt-dev libgflags-dev zlib1g-dev patchelf
pip3 install packaging ninja cpufeature numpy openai
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126
```
### 3. Build with Balance Serve Support
```bash
# Install single NUMA dependencies
USE_BALANCE_SERVE=1 bash ./install.sh
# For those who have two cpu and 1T RAMDual NUMA:
USE_BALANCE_SERVE=1 USE_NUMA=1 bash ./install.sh
```
### 4. Run LLaMA 4 Inference Server
Make sure you have:
- `--model_path` pointing to a local config directory (not a Hugging Face name).
- `--gguf_path` pointing to quantized `.gguf` weights.
```bash
python ktransformers/server/main.py \
--port 10002 \
--model_path <path_to_safetensor_config> \
--gguf_path <path_to_gguf_files> \
--optimize_config_path ktransformers/optimize/optimize_rules/Llama4-serve.yaml \
--max_new_tokens 1024 \
--cache_lens 32768 \
--chunk_size 256 \
--max_batch_size 4 \
--backend_type balance_serve \
```
### 5. Access server
```
curl -X POST http://localhost:10002/v1/chat/completions \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '{
"messages": [
{"role": "user", "content": "hello"}
],
"model": "Llama4",
"temperature": 0.3,
"top_p": 1.0,
"stream": true
}'
```
------
## 📌 Limitations
- ✅ **Only `balance_serve` backend is supported** for LLaMA 4 models in this version.
- ⚠️ Requires **`transformers==4.51.0`** or newer. Due to potential compatibility issues with older toolchains, we have **not merged this branch to main yet**.
- ❌ Multimodal models are not supported yet in this version. Support will be added in future releases.