Text Generation
MLX
Safetensors
English
llama
music
art
text-generation-inference
mlx-my-repo
4-bit precision
Instructions to use mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx" --prompt "Once upon a time"
- Atomic Chat
mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx
The Model mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx was converted to MLX format from m-a-p/YuE-s1-7B-anneal-en-icl using mlx-lm version 0.20.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
- Downloads last month
- 16
Model size
6B params
Tensor type
U32
·
F16 ·
Hardware compatibility
Log In to add your hardware
4-bit
Model tree for mingz2022/YuE-s1-7B-anneal-en-icl-Q4-mlx
Base model
m-a-p/YuE-s1-7B-anneal-en-icl