Instructions to use telecomadm1145/test3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use telecomadm1145/test3 with KerasHub:
import keras_hub # Load CausalLM model (optional: use half precision for inference) causal_lm = keras_hub.models.CausalLM.from_preset("hf://telecomadm1145/test3", 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://telecomadm1145/test3") - Keras
How to use telecomadm1145/test3 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://telecomadm1145/test3") - Notebooks
- Google Colab
- Kaggle
| { | |
| "module": "keras_hub.src.models.qwen3.qwen3_causal_lm", | |
| "class_name": "Qwen3CausalLM", | |
| "config": { | |
| "backbone": { | |
| "module": "keras_hub.src.models.qwen3.qwen3_backbone", | |
| "class_name": "Qwen3Backbone", | |
| "config": { | |
| "name": "qwen3_backbone", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "float32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "vocabulary_size": 151936, | |
| "num_layers": 36, | |
| "num_query_heads": 32, | |
| "hidden_dim": 2560, | |
| "head_dim": 128, | |
| "intermediate_dim": 9728, | |
| "rope_max_wavelength": 1000000, | |
| "rope_scaling_factor": 1.0, | |
| "num_key_value_heads": 8, | |
| "layer_norm_epsilon": 1e-06, | |
| "dropout": 0.0, | |
| "tie_word_embeddings": true, | |
| "sliding_window_size": null | |
| }, | |
| "registered_name": "keras_hub>Qwen3Backbone" | |
| }, | |
| "preprocessor": { | |
| "module": "keras_hub.src.models.qwen3.qwen3_causal_lm_preprocessor", | |
| "class_name": "Qwen3CausalLMPreprocessor", | |
| "config": { | |
| "name": "qwen3_causal_lm_preprocessor", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "float32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "tokenizer": { | |
| "module": null, | |
| "class_name": "HFRustTokenizerWrapper", | |
| "config": { | |
| "name": "hf_rust_tokenizer_wrapper", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "float32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "config_file": "tokenizer.json" | |
| }, | |
| "registered_name": "HFRustTokenizerWrapper" | |
| }, | |
| "config_file": "preprocessor.json", | |
| "sequence_length": 2048, | |
| "add_start_token": false, | |
| "add_end_token": true | |
| }, | |
| "registered_name": "keras_hub>Qwen3CausalLMPreprocessor" | |
| }, | |
| "name": "qwen3_causal_lm" | |
| }, | |
| "registered_name": "keras_hub>Qwen3CausalLM" | |
| } |