ModelPrésentéExterne

LLaMA Mesh Q4 Mlx

The Model alexgusevski/LLaMA-Mesh-q4-mlx was converted to MLX format from Zhengyi/LLaMA-Mesh using mlx-lm version 0.21.4.

Sourcehuggingface.co/alexgusevski/LLaMA-Mesh-q4-mlx/tree/ca78b57db5157436e70946219a9bf94eaaddba3c

TypeText modelModèle de baseZhengyi/LLaMA-MeshVersionmodelBClasse

Source du modèle

Type: Text model
Taille du fichier: 4,21 GB
Modèle de base: Zhengyi/LLaMA-Mesh
Version: vmodel
Mis à jour: 10 oct. 2026
Téléchargements: 26
Source: Hugging Face

Description de la source

alexgusevski/LLaMA-Mesh-q4-mlx

The Model alexgusevski/LLaMA-Mesh-q4-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-q4-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 ca78b57db5157436e70946219a9bf94eaaddba3c

huggingface.co/alexgusevski/LLaMA-Mesh-q4-mlx/tree/ca78b57db5157436e70946219a9bf94eaaddba3c

Vérifié 10 oct.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 4,21 GB · SHA-256 951e1893e7f5…110e · Hugging Face

Download file

Extraits de sources

3 extraits

Readme1 aoûthuggingface.co/alexgusevski/LLaMA-Mesh-q4-mlx

--- license: llama3.1 library_name: transformers pipeline_tag: text-to-3d tags: - mesh-generation - mlx base_model: Zhengyi/LLaMA-Mesh --- # alexgusevski/LLaMA-Mesh-q4-mlx The Model [alexgusevski/LLaMA-Mesh-q4-mlx](https://huggingface.co/alexgusevski/LLaMA-Mesh-q4-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-q4-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-q4-mlx

Source context: 26 downloads · 2 likes · Pipeline text-to-3d · Library transformers · Repo alexgusevski/LLaMA-Mesh-q4-mlx

Note1 aoûthuggingface.co/alexgusevski/LLaMA-Mesh-q4-mlx

Source context: 13 downloads · 2 likes · Pipeline text-to-3d · Library transformers · Repo alexgusevski/LLaMA-Mesh-q4-mlx