diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -20,6 +20,7 @@
- **Local UI:** Streamlit for interactive model deployment and testing
## Latest News 🔥
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- Support Nexa AI's own vision language model (0.9B parameters): `nexa run omnivision` and audio language model (2.9B parameters): `nexa run omniaudio`
- Support audio language model: `nexa run qwen2audio`, **we are the first open-source toolkit to support audio language model with GGML tensor library.**
- Support iOS Swift binding for local inference on **iOS mobile** devices.
@@ -32,13 +33,13 @@ Welcome to submit your requests through [issues](https://github.com/NexaAI/nexa-
## Install Option 1: Executable Installer
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+
macOS Installer
-
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Windows Installer
@@ -205,18 +206,18 @@ pip install -e .
Below is our differentiation from other similar tools:
-| **Feature** | **[Nexa SDK](https://github.com/NexaAI/nexa-sdk)** | **[ollama](https://github.com/ollama/ollama)** | **[Optimum](https://github.com/huggingface/optimum)** | **[LM Studio](https://github.com/lmstudio-ai)** |
-| -------------------------- | :------------------------------------------------: | :--------------------------------------------: | :---------------------------------------------------: | :---------------------------------------------: |
-| **GGML Support** | ✅ | ✅ | ❌ | ✅ |
-| **ONNX Support** | ✅ | ❌ | ✅ | ❌ |
-| **Text Generation** | ✅ | ✅ | ✅ | ✅ |
-| **Image Generation** | ✅ | ❌ | ❌ | ❌ |
-| **Vision-Language Models** | ✅ | ✅ | ✅ | ✅ |
-| **Audio-Language Models** | ✅ | ❌ | ❌ | ❌ |
-| **Text-to-Speech** | ✅ | ❌ | ✅ | ❌ |
-| **Server Capability** | ✅ | ✅ | ✅ | ✅ |
-| **User Interface** | ✅ | ❌ | ❌ | ✅ |
-| **Executable Installation** | ✅ | ✅ | ❌ | ✅ |
+| **Feature** | **[Nexa SDK](https://github.com/NexaAI/nexa-sdk)** | **[ollama](https://github.com/ollama/ollama)** | **[Optimum](https://github.com/huggingface/optimum)** | **[LM Studio](https://github.com/lmstudio-ai)** |
+| --------------------------- | :------------------------------------------------: | :--------------------------------------------: | :---------------------------------------------------: | :---------------------------------------------: |
+| **GGML Support** | ✅ | ✅ | ❌ | ✅ |
+| **ONNX Support** | ✅ | ❌ | ✅ | ❌ |
+| **Text Generation** | ✅ | ✅ | ✅ | ✅ |
+| **Image Generation** | ✅ | ❌ | ❌ | ❌ |
+| **Vision-Language Models** | ✅ | ✅ | ✅ | ✅ |
+| **Audio-Language Models** | ✅ | ❌ | ❌ | ❌ |
+| **Text-to-Speech** | ✅ | ❌ | ✅ | ❌ |
+| **Server Capability** | ✅ | ✅ | ✅ | ✅ |
+| **User Interface** | ✅ | ❌ | ❌ | ✅ |
+| **Executable Installation** | ✅ | ✅ | ❌ | ✅ |
## Supported Models & Model Hub
@@ -257,25 +258,37 @@ Supported model examples (full list at [Model Hub](https://nexa.ai/models)):
| [bark-small](https://nexa.ai/suno/bark-small/gguf-fp16/readme) | Text-to-Speech | GGUF | `nexa run bark-small:fp16` |
## Run Models from 🤗 HuggingFace or 🤖 ModelScope
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You can pull, convert (to .gguf), quantize and run [llama.cpp supported](https://github.com/ggerganov/llama.cpp#description) text generation models from HF or MS with Nexa SDK.
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### Run .gguf File
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Use `nexa run -hf ` or `nexa run -ms ` to run models with provided .gguf files:
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```bash
nexa run -hf Qwen/Qwen2.5-Coder-7B-Instruct-GGUF
```
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```bash
nexa run -ms Qwen/Qwen2.5-Coder-7B-Instruct-GGUF
```
+
> **Note:** You will be prompted to select a single .gguf file. If your desired quantization version has multiple split files (like fp16-00001-of-00004), please use Nexa's conversion tool (see below) to convert and quantize the model locally.
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### Convert .safetensors Files
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Install [Nexa Python package](https://github.com/NexaAI/nexa-sdk?tab=readme-ov-file#install-option-2-python-package), and install Nexa conversion tool with `pip install "nexaai[convert]"`, then convert models from huggingface with `nexa convert `:
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```bash
nexa convert HuggingFaceTB/SmolLM2-135M-Instruct
```
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Or you can convert models from ModelScope with `nexa convert -ms `:
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```bash
nexa convert -ms Qwen/Qwen2.5-7B-Instruct
```
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> **Note:** Check our [leaderboard](https://nexa.ai/leaderboard) for performance benchmarks of different quantized versions of mainstream language models and [HuggingFace docs](https://huggingface.co/docs/optimum/en/concept_guides/quantization) to learn about quantization options.
📋 You can view downloaded and converted models with `nexa list`