Instructions to use alfonsodlg/celulares-gemma3-4b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use alfonsodlg/celulares-gemma3-4b-gguf with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("alfonsodlg/celulares-gemma3-4b-gguf", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use alfonsodlg/celulares-gemma3-4b-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M

Use Docker

docker model run hf.co/alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use alfonsodlg/celulares-gemma3-4b-gguf with Ollama:
```
ollama run hf.co/alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use alfonsodlg/celulares-gemma3-4b-gguf with Docker Model Runner:
```
docker model run hf.co/alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M
```

Lemonade

How to use alfonsodlg/celulares-gemma3-4b-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull alfonsodlg/celulares-gemma3-4b-gguf:Q4_K_M

Run and chat with the model

lemonade run user.celulares-gemma3-4b-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

alfonsodlg commited on Dec 8, 2025

Commit

6a61b60

verified ·

1 Parent(s): e66df8d

Upload folder using huggingface_hub

Browse files

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+---
+license: apache-2.0
+language:
+- es
+library_name: transformers
+tags:
+- gemma
+- gguf
+- sales
+- conversational
+- spanish
+- fine-tuned
+base_model: google/gemma-3-4b-it
+model_type: gemma3
+quantization: Q4_K_M
+---
+# 🤖 Celulares Gemma 3 4B v3 - Agente de Ventas (GGUF Q4_K_M)
+Modelo Gemma 3 4B fine-tuned para ventas de celulares en español peruano.
+## 📊 Especificaciones
+| Parámetro | Valor |
+|-----------|-------|
+| Modelo base | google/gemma-3-4b-it |
+| Cuantización | Q4_K_M (4-bit) |
+| Tamaño | 2.4 GB |
+| Idioma | Español (Perú) |
+| Contexto | 4,096 tokens |
+| Dataset | 1,017 conversaciones |
+## 🎯 Uso
+### Con Ollama
+```bash
+# Descargar el archivo GGUF
+wget https://huggingface.co/alfonsodlg/celulares-gemma3-4b-gguf/resolve/main/celulares-v3-q4_k_m.gguf
+# Crear Modelfile
+cat > Modelfile << 'MODELFILE'
+FROM ./celulares-v3-q4_k_m.gguf
+TEMPLATE "<start_of_turn>user
+{{ .Prompt }}<end_of_turn>
+<start_of_turn>model
+{{ .Response }}<end_of_turn>
+"
+SYSTEM "Eres un agente de ventas experto en celulares de Coolbox Perú. Tu personalidad es entusiasta, consultiva y orientada a resultados."
+PARAMETER temperature 0.1
+PARAMETER top_p 0.9
+PARAMETER num_ctx 4096
+PARAMETER stop "<end_of_turn>"
+MODELFILE
+# Importar a Ollama
+ollama create celulares:v3-q4 -f Modelfile
+```
+### Ejemplo de uso
+```python
+import requests
+response = requests.post('http://localhost:11434/api/generate', json={
+    'model': 'celulares:v3-q4',
+    'prompt': 'Busco un celular Samsung hasta 1500 soles',
+    'stream': False
+})
+print(response.json()['response'])
+```
+## 📈 Métricas
+- **Tasa de éxito**: 100% (9/9 tests críticos)
+- **Latencia**: 3-8 segundos (respuesta completa)
+- **RAM**: ~4GB
+## 🏋️ Entrenamiento
+- **Plataforma**: Modal (H100)
+- **Framework**: Unsloth
+- **Dataset**: 1,017 conversaciones de ventas
+- **Steps**: 200
+- **Loss final**: ~0.4
+## 📝 Licencia
+Apache 2.0
+## 🔗 Enlaces
+- [Repositorio del proyecto](https://github.com/alfonsodlg/pricex-smart)
+- [Modelo base Gemma 3](https://huggingface.co/google/gemma-3-4b-it)

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