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zai-org/glm-4-9b-chat-1m-hf for kerasformers. One implementation runs unmodified on TensorFlow / Torch / JAX. This is a GLM-4-9B checkpoint served as text -> text; weights are stored in bfloat16.1import os
2os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
3
4from kerasformers.models.glm import GlmTextGenerate, GlmTokenizer
5
6model = GlmTextGenerate.from_weights("kerasformers/glm-4-9b-chat-1m")
7tokenizer = GlmTokenizer.from_weights("kerasformers/glm-4-9b-chat-1m")
8
9messages = [{"role": "user", "content": "Name three prime numbers."}]
10inputs = tokenizer(messages)
11outputs = model.generate(**inputs, max_new_tokens=128)
12print(tokenizer.decode(outputs[0]))from_weights("kerasformers/<variant>"). Browse them all in the GLM collection.