metadata
language:
- en
library_name: transformers
tags:
- glm
- glm4
- MOE
- pruning
- compression
- reap
- cerebras
- code
- function-calling
- agentic
- mlx
- mlx-my-repo
license: apache-2.0
pipeline_tag: text-generation
base_model: 0xSero/GLM-4.7-REAP-40
thejson/GLM-4.7-REAP-40-mlx-4Bit
The Model thejson/GLM-4.7-REAP-40-mlx-4Bit was converted to MLX format from 0xSero/GLM-4.7-REAP-40 using mlx-lm version 0.29.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("thejson/GLM-4.7-REAP-40-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)