How to use from
Hermes AgentConfigure Hermes
# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default kernelpool/GLM-5.1-8bitRun Hermes
hermesQuick Links
kernelpool/GLM-5.1-8bit
This model kernelpool/GLM-5.1-8bit was converted to MLX format from zai-org/GLM-5.1 using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("kernelpool/GLM-5.1-8bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model size
744B params
Tensor type
BF16
·
U32 ·
F32 ·
Hardware compatibility
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8-bit
Model tree for kernelpool/GLM-5.1-8bit
Base model
zai-org/GLM-5.1
Start the MLX server
# Install MLX LM: uv tool install mlx-lm# Start a local OpenAI-compatible server: mlx_lm.server --model "kernelpool/GLM-5.1-8bit"