Instructions to use keras/qwen3_embedding_8b_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/qwen3_embedding_8b_en with KerasHub:
import keras_hub # Load CausalLM model (optional: use half precision for inference) causal_lm = keras_hub.models.CausalLM.from_preset("hf://keras/qwen3_embedding_8b_en", 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/qwen3_embedding_8b_en") - Keras
How to use keras/qwen3_embedding_8b_en with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://keras/qwen3_embedding_8b_en") - Notebooks
- Google Colab
- Kaggle
File size: 190 Bytes
2c4348c | 1 2 3 4 5 6 7 8 9 | {
"keras_version": "3.11.3",
"keras_hub_version": "0.23.0.dev0",
"parameter_count": 8188515328,
"date_saved": "2025-11-13@23:21:46",
"tasks": [
"CausalLM"
]
} |