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Model: daniloreddy/gemma-3-270m-it_GGUF
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+base_model: google/gemma-3-270m
+tags:
+- llama.cpp
+- gguf
+- quantized
+- text-generation
+- lightweight
+- lmstudio
+- jan
+- cobalt
+- text-generation-webui
+---
+
+# Gemma-3-270m-IT - GGUF High-Quality Quantizations
+
+This repository provides **GGUF** quantized versions of the [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it) model, optimized for local execution using `llama.cpp` and compatible ecosystems.
+
+## 📌 Version Notes
+All quantizations were generated from the official **FP16** weights.
+- **Target:** Efficient execution on consumer hardware, mobile/edge devices, and systems with limited memory.
+- **Performance:** The output quality (reasoning, coherence, and accuracy) is strictly dependent on the base model's parameter scale (270M).
+
+## 📊 Quantization Table
+
+| File | Method | Bit | Description |
+| :--- | :--- | :--- | :--- |
+| **fp16.gguf** | FP16 | 16-bit | **Original Weights.** No quantization applied. Maximum fidelity. |
+| **Q8_0.gguf** | Q8_0 | 8-bit | **Near-lossless.** Practically identical to the original model with lower memory footprint. |
+| **Q5_K_M.gguf** | Q5_K_M | 5-bit | **High Precision.** Minimizes quantization error for critical tasks. |
+| **Q4_K_M.gguf** | Q4_K_M | 4-bit | **Recommended.** Best balance between speed and performance. |
+| **Q4_K_S.gguf** | Q4_K_S | 4-bit | **Fast/Small.** Optimized for maximum throughput and low RAM usage. |
+
+## 🛠️ Technical Details
+- **Quantization Date:** 2026-03-07
+- **Tool used:** `llama-quantize` (llama.cpp)
+- **Method:** K-Quantization (optimized for AVX2/AVX-512 and modern GPU architectures).
+
+## 🚀 How to Use
+# Start a local OpenAI-compatible server with a web UI:
+
+### llama.cpp (CLI) using model from HuggingFace
+```bash
+./llama-cli -hf daniloreddy/gemma-3-270m-it_GGUF:Q4_K_M -p "User: Hello! Assistant:" -n 512 --temp 0.7
+```
+
+### llama.cpp (CLI) using downloaded model
+```bash
+./llama-cli -m path/to/gemma-3-270m-it_Q4_K_M.gguf -p "User: Hello! Assistant:" -n 512 --temp 0.7
+```
+
+### llama.cpp (SERVER) using model from HuggingFace
+```bash
+./llama-server -hf daniloreddy/gemma-3-270m-it_GGUF:Q4_K_M --port 8080 -c 4096
+```
+
+### llama.cpp (SERVER) using downloaded model
+```bash
+./llama-server -m /path/to/gemma-3-270m-it_Q4_K_M.gguf --port 8080 -c 4096
+```

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