Instructions to use Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit --local-dir GLM-4.5-Iceblink-106B-A12B-mlx-4Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit: direct link, hf CLI and curl.
- Browser
- Download file 1.07 kB
-
https://huggingface.co/Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit/resolve/main/README.md
- Command line
-
hf download hf://Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit/README.md
-
curl -L -o README.md https://huggingface.co/Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit/resolve/main/README.md
1.07 kB
metadata
license: mit
datasets:
- zerofata/Instruct-Anime
- zerofata/Roleplay-Anime-Characters
- zerofata/Instruct-Anime-CreativeWriting
- zerofata/Summaries-Anime-FandomPages
base_model: zerofata/GLM-4.5-Iceblink-106B-A12B
tags:
- mlx
Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit
The Model Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit was converted to MLX format from zerofata/GLM-4.5-Iceblink-106B-A12B using mlx-lm version 0.26.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Wwayu/GLM-4.5-Iceblink-106B-A12B-mlx-4Bit")
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)