ModelPrésentéExterne

LLaMA Mesh Q3 Mlx

The Model alexgusevski/LLaMA-Mesh-q3-mlx was converted to MLX format from Zhengyi/LLaMA-Mesh using mlx-lm version 0.21.4.

Sourcehuggingface.co/alexgusevski/LLaMA-Mesh-q3-mlx/tree/318dab9eb07a611d13e2c44bf76ee126f09fa66d

TypeText modelModèle de baseZhengyi/LLaMA-MeshVersionmodelBClasse

Source du modèle

Type: Text model
Taille du fichier: 3,27 GB
Modèle de base: Zhengyi/LLaMA-Mesh
Version: vmodel
Mis à jour: 10 oct. 2026
Téléchargements: 18
Source: Hugging Face

Description de la source

alexgusevski/LLaMA-Mesh-q3-mlx

The Model alexgusevski/LLaMA-Mesh-q3-mlx was converted to MLX format from Zhengyi/LLaMA-Mesh using mlx-lm version 0.21.4.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("alexgusevski/LLaMA-Mesh-q3-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Sources

1 source

Hugging FacePrincipalVersion 318dab9eb07a611d13e2c44bf76ee126f09fa66d

huggingface.co/alexgusevski/LLaMA-Mesh-q3-mlx/tree/318dab9eb07a611d13e2c44bf76ee126f09fa66d

Vérifié 10 oct.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 3,27 GB · SHA-256 59a00cde8988…4ea2 · Hugging Face

Download file

Extraits de sources

3 extraits

Readme1 aoûthuggingface.co/alexgusevski/LLaMA-Mesh-q3-mlx

--- license: llama3.1 library_name: transformers pipeline_tag: text-to-3d tags: - mesh-generation - mlx base_model: Zhengyi/LLaMA-Mesh --- # alexgusevski/LLaMA-Mesh-q3-mlx The Model [alexgusevski/LLaMA-Mesh-q3-mlx](https://huggingface.co/alexgusevski/LLaMA-Mesh-q3-mlx) was converted to MLX format from [Zhengyi/LLaMA-Mesh](https://huggingface.co/Zhengyi/LLaMA-Mesh) using mlx-lm version **0.21.4**. ## Use with mlx ```bash pip install mlx-lm ``` ```python from mlx_lm import load, generate model, tokenizer = load("alexgusevski/LLaMA-Mesh-q3-mlx") prompt = "hello" if tokenizer.chat_template is not None: messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) response = generate(model, tokenizer, prompt=prompt, verbose=True) ```

Note10 oct.huggingface.co/alexgusevski/LLaMA-Mesh-q3-mlx

Source context: 18 downloads · 0 likes · Pipeline text-to-3d · Library transformers · Repo alexgusevski/LLaMA-Mesh-q3-mlx

Note1 aoûthuggingface.co/alexgusevski/LLaMA-Mesh-q3-mlx

Source context: 8 downloads · 0 likes · Pipeline text-to-3d · Library transformers · Repo alexgusevski/LLaMA-Mesh-q3-mlx