Upload model via QuantLLM

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README.md

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+---
+license: apache-2.0
+base_model: google/functiongemma-270m-it
+library_name: gguf
+language:
+  - en
+tags:
+  - quantllm
+  - gguf
+  - llama-cpp
+  - quantized
+  - transformers
+  - q4_k_m
+---
+
+<div align="center">
+
+# 🦙 functiongemma-270m-it-4bit-gguf
+
+**google/functiongemma-270m-it** converted to **GGUF** format
+
+[![QuantLLM](https://img.shields.io/badge/🚀_Made_with-QuantLLM-orange?style=for-the-badge)](https://github.com/codewithdark-git/QuantLLM)
+[![Format](https://img.shields.io/badge/Format-GGUF-blue?style=for-the-badge)]()
+[![Quantization](https://img.shields.io/badge/Quant-Q4_K_M-green?style=for-the-badge)]()
+
+<a href="https://github.com/codewithdark-git/QuantLLM">⭐ Star QuantLLM on GitHub</a>
+
+</div>
+
+---
+
+
+## 📖 About This Model
+
+This model is **[google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it)** converted to **GGUF** format for use with llama.cpp, Ollama, LM Studio, and other compatible inference engines.
+
+| Property | Value |
+|----------|-------|
+| **Base Model** | [google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it) |
+| **Format** | GGUF |
+| **Quantization** | Q4_K_M |
+| **License** | apache-2.0 |
+| **Created With** | [QuantLLM](https://github.com/codewithdark-git/QuantLLM) |
+
+
+## 🚀 Quick Start
+
+### Option 1: Python (llama-cpp-python)
+
+```python
+from llama_cpp import Llama
+
+# Load the model
+llm = Llama.from_pretrained(
+    repo_id="QuantLLM/functiongemma-270m-it-4bit-gguf",
+    filename="functiongemma-270m-it-4bit-gguf.Q4_K_M.gguf",
+)
+
+# Generate text
+output = llm(
+    "Write a short story about a robot learning to paint:",
+    max_tokens=256,
+    echo=True
+)
+print(output["choices"][0]["text"])
+```
+
+### Option 2: Ollama
+
+```bash
+# Download the model
+huggingface-cli download QuantLLM/functiongemma-270m-it-4bit-gguf functiongemma-270m-it-4bit-gguf.Q4_K_M.gguf --local-dir .
+
+# Create Modelfile
+echo 'FROM ./functiongemma-270m-it-4bit-gguf.Q4_K_M.gguf' > Modelfile
+
+# Import to Ollama
+ollama create functiongemma-270m-it-4bit-gguf -f Modelfile
+
+# Chat with the model
+ollama run functiongemma-270m-it-4bit-gguf
+```
+
+### Option 3: LM Studio
+
+1. Download the `.gguf` file from the **Files** tab above
+2. Open **LM Studio** → **My Models** → **Add Model**
+3. Select the downloaded file
+4. Start chatting!
+
+### Option 4: llama.cpp CLI
+
+```bash
+# Download
+huggingface-cli download QuantLLM/functiongemma-270m-it-4bit-gguf functiongemma-270m-it-4bit-gguf.Q4_K_M.gguf --local-dir .
+
+# Run inference
+./llama-cli -m functiongemma-270m-it-4bit-gguf.Q4_K_M.gguf -p "Hello! " -n 128
+```
+
+
+## 📊 Model Details
+
+| Property | Value |
+|----------|-------|
+| **Original Model** | [google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it) |
+| **Format** | GGUF |
+| **Quantization** | Q4_K_M |
+| **License** | `apache-2.0` |
+| **Export Date** | 2025-12-21 |
+| **Exported By** | [QuantLLM v2.0](https://github.com/codewithdark-git/QuantLLM) |
+
+
+## 📦 Quantization Details
+
+This model uses **Q4_K_M** quantization:
+
+| Property | Value |
+|----------|-------|
+| **Type** | Q4_K_M |
+| **Bits** | 4-bit |
+| **Quality** | 🟢 ⭐ Recommended - Best quality/size balance |
+
+### All Available GGUF Quantizations
+
+| Type | Bits | Quality | Best For |
+|------|------|---------|----------|
+| Q2_K | 2-bit | 🔴 Lowest | Extreme size constraints |
+| Q3_K_M | 3-bit | 🟠 Low | Very limited memory |
+| Q4_K_M | 4-bit | 🟢 Good | **Most users** ⭐ |
+| Q5_K_M | 5-bit | 🟢 High | Quality-focused |
+| Q6_K | 6-bit | 🔵 Very High | Near-original |
+| Q8_0 | 8-bit | 🔵 Excellent | Maximum quality |
+
+
+---
+
+## 🚀 Created with QuantLLM
+
+<div align="center">
+
+[![QuantLLM](https://img.shields.io/badge/🚀_QuantLLM-Ultra--fast_LLM_Quantization-orange?style=for-the-badge)](https://github.com/codewithdark-git/QuantLLM)
+
+**Convert any model to GGUF, ONNX, or MLX in one line!**
+
+```python
+from quantllm import turbo
+
+# Load any HuggingFace model
+model = turbo("google/functiongemma-270m-it")
+
+# Export to any format
+model.export("gguf", quantization="Q4_K_M")
+
+# Push to HuggingFace
+model.push("your-repo", format="gguf")
+```
+
+<a href="https://github.com/codewithdark-git/QuantLLM">
+  <img src="https://img.shields.io/github/stars/codewithdark-git/QuantLLM?style=social" alt="GitHub Stars">
+</a>
+
+**[📚 Documentation](https://github.com/codewithdark-git/QuantLLM#readme)** · 
+**[🐛 Report Issue](https://github.com/codewithdark-git/QuantLLM/issues)** · 
+**[💡 Request Feature](https://github.com/codewithdark-git/QuantLLM/issues)**
+
+</div>

functiongemma-270m-it.Q4_K_M.gguf

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