Instructions to use Pier-Jean/tiny-qwen3-llvq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pier-Jean/tiny-qwen3-llvq with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Pier-Jean/tiny-qwen3-llvq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
tiny-qwen3-llvq
A one-layer Qwen3 of 148 KB in the LLVQ format, for tests. Its weights mean nothing.
It has lattice layers, 4-bit layers, a rotation and a 4-bit embedding, so loading it goes through every part of the
format. It is the fixture llvq-tetra/tests/fixtures/mini of
github.com/pjmalandrino/llvq, written by the Rust test
the_mini_fixture_describes_a_whole_qwen3_layer.
pip install llvq-tetra
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Pier-Jean/tiny-qwen3-llvq")
- Downloads last month
- -
Inference Providers NEW
This model isn't deployed by any Inference Provider. 馃檵 Ask for provider support