How to use from the
Use from the
llama-cpp-python library
# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Krasty/agentify-extraction-q3_k",
	filename="models_gemma_extraction_v1-Q3_K.gguf",
)
llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Krasty/agentify-extraction-q3_k

Извлечение структурированных полей в JSON.

Quantization

  • Q3_K

Files

  • models_gemma_extraction_v1-Q3_K.gguf

Recommended system behavior

Верни только валидный JSON-объект строкой, без markdown и пояснений.

Usage (Ollama)

ollama create extraction -f Modelfile

Where Modelfile:

FROM ./models_gemma_extraction_v1-Q3_K.gguf
Downloads last month
1
GGUF
Model size
5B params
Architecture
gemma4
Hardware compatibility
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