Downloads · 30 days
34
6% of all-time downloads
mrtoots/GLM-4.7-REAP-218B-A32B-mlx-4Bit
GLM-4.7-REAP-218B-A32B-mlx-4Bit is a text generation model from mrtoots. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
The Model mrtoots/GLM-4.7-REAP-218B-A32B-mlx-4Bit was converted to MLX format from unsloth/GLM-4.7-REAP-218B-A32B using mlx-lm version 0.29.1.
Downloads · 30 days
34
6% of all-time downloads
All-time downloads
564
Public
Parameters
218B
123 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors123 GB · 100%
How the weights are stored.
U32218B · 100%
From the Hugging Face model README
The Model mrtoots/GLM-4.7-REAP-218B-A32B-mlx-4Bit was converted to MLX format from unsloth/GLM-4.7-REAP-218B-A32B using mlx-lm version 0.29.1.
This model was converted and quantized utilizing unsloth's version of GLM-4.7-REAP-218B-A32B from Cerebras. Should include any chat template fixes.
Please follow and support Cerebras' work and unsloth's work if you like it!
🦛 <span style="color:#800080">If you want a free consulting session, </span>fill out this form <span style="color:#800080">to get in touch!</span> 🤗
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mrtoots/GLM-4.7-REAP-218B-A32B-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)