Instructions to use keras/qwen2.5_coder_32b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/qwen2.5_coder_32b with KerasHub:
import keras_hub # Load CausalLM model (optional: use half precision for inference) causal_lm = keras_hub.models.CausalLM.from_preset("hf://keras/qwen2.5_coder_32b", dtype="bfloat16") causal_lm.compile(sampler="greedy") # (optional) specify a sampler # Generate text causal_lm.generate("Keras: deep learning for", max_length=64)import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/qwen2.5_coder_32b") - Keras
How to use keras/qwen2.5_coder_32b with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/qwen2.5_coder_32b") - Notebooks
- Google Colab
- Kaggle
| { | |
| "keras_version": "3.12.0", | |
| "keras_hub_version": "0.26.0.dev0", | |
| "parameter_count": 32763876352, | |
| "date_saved": "2026-01-28@21:18:19", | |
| "tasks": [ | |
| "CausalLM" | |
| ] | |
| } |