Qwen3-Next
Collection
Pure-Keras 3 conversions of Qwen3-Next-80B-A3B (kerasformers). • 2 items • Updated
How to use zeromodels/qwen3-next-80b-a3b-thinking with Keras:
# Available backend options are: "jax", "torch", "tensorflow".
import os
os.environ["KERAS_BACKEND"] = "jax"
import keras
model = keras.saving.load_model("hf://zeromodels/qwen3-next-80b-a3b-thinking")
Pure-Keras 3 conversion of Qwen/Qwen3-Next-80B-A3B-Thinking for zeromodels. One implementation runs unmodified on TensorFlow / Torch / JAX. Qwen3-Next is a Gated-DeltaNet + MoE hybrid; weights are stored in bfloat16.
For model details, license, and usage terms, see the upstream model card.
Paper: Qwen3 Technical Report (arXiv:2505.09388) · HF Papers
Paper: Qwen2.5-1M Technical Report (arXiv:2501.15383) · HF Papers
Paper: YaRN: Efficient Context Window Extension of Large Language Models (arXiv:2309.00071) · HF Papers
import os
os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
from zeromodels.models.qwen3_next import Qwen3NextTextGenerate, Qwen3NextTokenizer
model = Qwen3NextTextGenerate.from_weights("zeromodels/qwen3-next-80b-a3b-thinking")
tokenizer = Qwen3NextTokenizer.from_weights("zeromodels/qwen3-next-80b-a3b-thinking")
inputs = tokenizer("Give me a short introduction to large language models.")
outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0]))
A huge thank you to the Qwen team at Alibaba for creating and releasing these models.
License: Apache 2.0.
Base model
Qwen/Qwen3-Next-80B-A3B-Thinking