Instructions to use keras/llama3.2_instruct_3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/llama3.2_instruct_3b with KerasHub:
import keras_hub # Create a LlamaCausalLM model task = keras_hub.models.LlamaCausalLM.from_preset("hf://keras/llama3.2_instruct_3b")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/llama3.2_instruct_3b") - Keras
How to use keras/llama3.2_instruct_3b 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/llama3.2_instruct_3b") - Notebooks
- Google Colab
- Kaggle
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a5f6185 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | {
"module": "keras_hub.src.models.llama3.llama3_causal_lm_preprocessor",
"class_name": "Llama3CausalLMPreprocessor",
"config": {
"name": "llama3_causal_lm_preprocessor",
"trainable": true,
"dtype": {
"module": "keras",
"class_name": "DTypePolicy",
"config": {
"name": "float32"
},
"registered_name": null
},
"tokenizer": {
"module": "keras_hub.src.models.llama3.llama3_tokenizer",
"class_name": "Llama3Tokenizer",
"config": {
"name": "llama3_tokenizer_1",
"trainable": true,
"dtype": {
"module": "keras",
"class_name": "DTypePolicy",
"config": {
"name": "int32"
},
"registered_name": null
},
"config_file": "tokenizer.json",
"sequence_length": null,
"add_prefix_space": false,
"unsplittable_tokens": [
"<|finetune_right_pad_id|>",
"<|python_tag|>",
"<|start_header_id|>",
"<|begin_of_text|>",
"<|end_header_id|>",
"<|end_of_text|>",
"<|eom_id|>",
"<|eot_id|>"
]
},
"registered_name": "keras_hub>Llama3Tokenizer"
},
"config_file": "preprocessor.json",
"sequence_length": 1024,
"add_start_token": true,
"add_end_token": true
},
"registered_name": "keras_hub>Llama3CausalLMPreprocessor"
} |