初始化项目，由ModelHub XC社区提供模型

Model: Swicked86/phi4-mm-gguf
Source: Original Platform

deploy/README-deployment.md

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+---
+license: mit
+base_model: microsoft/Phi-4-multimodal-instruct
+tags:
+  - phi4mm
+  - gguf
+  - quantized
+  - q4_k_m
+  - cpu
+  - ollama
+  - llama-cpp
+language:
+  - multilingual
+  - ar
+  - zh
+  - cs
+  - da
+  - nl
+  - en
+  - fi
+  - fr
+  - de
+  - he
+  - hu
+  - it
+  - ja
+  - ko
+  - "no"
+  - pl
+  - pt
+  - ru
+  - es
+  - sv
+  - th
+  - tr
+  - uk
+pipeline_tag: text-generation
+---
+
+# Phi-4 Multimodal Instruct — GGUF Quantizations
+
+CPU-optimised GGUF quantizations of [microsoft/Phi-4-multimodal-instruct](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) produced with [llama.cpp](https://github.com/ggerganov/llama.cpp).
+
+## Model Summary
+
+Phi-4-multimodal-instruct is a **5.6 B parameter** lightweight multimodal foundation model by Microsoft that processes text, image, and audio inputs. The backbone LLM is **Phi-4-Mini** (3.8 B). This repository contains GGUF quantizations for local CPU and GPU deployment.
+
+- **Context length:** 128 K tokens (131 072)
+- **Architecture:** `phi3` (GGUF)  
+- **License:** [MIT](https://huggingface.co/microsoft/Phi-4-multimodal-instruct/blob/main/LICENSE) — © Microsoft Corporation
+
+## Available Files
+
+| File | Quant | Size | BPW | Best for |
+|------|-------|------|-----|----------|
+| `phi4-mm-Q4_K_M.gguf` | Q4_K_M | 2.37 GB | 5.18 | CPU inference, 8 GB RAM systems |
+| `phi4-mm-Q8_0.gguf`   | Q8_0   | 3.90 GB | 8.00 | GPU/high-RAM systems, near-lossless |
+| `phi4-mm-f16.gguf`    | F16    | 7.17 GB  | 16.00 | Source / re-quantization base |
+
+## Quantization Method
+
+Quantized using `llama-quantize` from [ggerganov/llama.cpp](https://github.com/ggerganov/llama.cpp) (build 8334).
+
+```bash
+llama-quantize phi4-mm-f16.gguf phi4-mm-Q4_K_M.gguf Q4_K_M 16
+```
+
+Source weights converted from the original safetensors using `convert_hf_to_gguf.py`.
+
+## Recommended Usage
+
+### Ollama (CPU — Intel NUC / low-power hardware)
+
+```bash
+# Pull and run (once uploaded to Ollama registry)
+ollama run phi4-mm-nuc
+
+# Or import from GGUF directly with a Modelfile:
+ollama create phi4-mm-nuc -f Modelfile
+ollama run phi4-mm-nuc
+```
+
+**Modelfile for 8 GB RAM / no GPU:**
+
+```
+FROM phi4-mm-Q4_K_M.gguf
+PARAMETER num_ctx 8192
+PARAMETER num_thread 8
+PARAMETER num_gpu 0
+PARAMETER flash_attn false
+PARAMETER temperature 0.7
+PARAMETER repeat_penalty 1.1
+SYSTEM "You are a helpful, accurate, and concise AI assistant."
+```
+
+### llama.cpp CLI (GPU, full quality)
+
+```bash
+./build/bin/llama-cli \
+  -m phi4-mm-Q8_0.gguf \
+  --ctx-size 65536 \
+  --flash-attn on \
+  --kv-offload \
+  -ngl 99 \
+  --threads 16
+```
+
+### OpenClaw Integration
+
+In `~/.openclaw/openclaw.json`:
+
+```json
+{
+  "agent": {
+    "model": "ollama/phi4-mm-nuc"
+  },
+  "modelConfigs": {
+    "ollama/phi4-mm-nuc": {
+      "provider": "ollama",
+      "model": "phi4-mm-nuc",
+      "baseUrl": "http://localhost:11434"
+    }
+  }
+}
+```
+
+## Hardware Notes
+
+| Hardware | Recommended quant | Context | Notes |
+|---|---|---|---|
+| Intel NUC 11th Gen, 8 GB RAM | Q4_K_M | 8 192 | CPU-only, `num_gpu 0` |
+| Laptop / desktop, 16 GB RAM | Q5_K_M or Q8_0 | 16 384 | CPU or iGPU |
+| GPU with ≥ 8 GB VRAM | Q8_0 or F16 | 32 768–65 536 | Full `-ngl 99` offload |
+
+## License
+
+This repository redistributes quantized weights derived from [microsoft/Phi-4-multimodal-instruct](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) under the original **MIT License**.
+
+```
+MIT License
+Copyright (c) Microsoft Corporation.
+```
+
+Quantization tooling (llama.cpp) is also MIT licensed. See [llama.cpp LICENSE](https://github.com/ggerganov/llama.cpp/blob/master/LICENSE).
+
+## Attribution
+
+- Original model: Microsoft Research  
+- Quantization: produced with [llama.cpp](https://github.com/ggerganov/llama.cpp) by Georgi Gerganov et al.  
+- Technical report: [arXiv:2503.01743](https://arxiv.org/abs/2503.01743)