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Glm4MoeLite

docs/source/en/model_doc/glm4_moe_lite.md

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This model was released on 2026-01-19 and added to Hugging Face Transformers on 2026-01-13.

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Glm4MoeLite

Glm4MoeLite (GLM-4.7-Flash) is a 30B-parameter mixture-of-experts model with approximately 3B active parameters per token, designed for lightweight deployment that balances performance and efficiency. It is part of the GLM-4.7 family and supports interleaved thinking capabilities.

The example below demonstrates how to generate text with [Pipeline] or the [AutoModelForCausalLM] class.

<hfoptions id="usage"> <hfoption id="Pipeline">
python
from transformers import pipeline


pipe = pipeline(
    task="text-generation",
    model="zai-org/GLM-4.7-Flash",
)
pipe("The key to efficient language models is")
</hfoption> <hfoption id="AutoModelForCausalLM">
python
from transformers import AutoModelForCausalLM, AutoTokenizer


tokenizer = AutoTokenizer.from_pretrained("zai-org/GLM-4.7-Flash")
model = AutoModelForCausalLM.from_pretrained(
    "zai-org/GLM-4.7-Flash",
    device_map="auto",
)
input_ids = tokenizer("The key to efficient language models is", return_tensors="pt").to(model.device)

output = model.generate(**input_ids, max_new_tokens=50)
print(tokenizer.decode(output[0], skip_special_tokens=True))
</hfoption> </hfoptions>

Glm4MoeLiteConfig

[[autodoc]] Glm4MoeLiteConfig

Glm4MoeLiteModel

[[autodoc]] Glm4MoeLiteModel - forward

Glm4MoeLiteForCausalLM

[[autodoc]] Glm4MoeLiteForCausalLM - forward