Instructions to use pzarzycki/hrm-text-1b-code-tools-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use pzarzycki/hrm-text-1b-code-tools-sft with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://pzarzycki/hrm-text-1b-code-tools-sft") - KerasHub
How to use pzarzycki/hrm-text-1b-code-tools-sft with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://pzarzycki/hrm-text-1b-code-tools-sft") - Keras
How to use pzarzycki/hrm-text-1b-code-tools-sft with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://pzarzycki/hrm-text-1b-code-tools-sft") - Notebooks
- Google Colab
- Kaggle
File size: 355 Bytes
ab083a7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"gradient_accumulation_steps": 8,
"micro_batch_size": 1,
"microbatch_steps": 38248,
"optimizer_steps": 4781,
"train": {
"requested_response_tokens": 10000000,
"selected_response_tokens": 10000147,
"selected_rows": 38248,
"selected_serialized_tokens": 19650833,
"shuffle_cycles_touched": 1,
"source_rows": 1133817
}
}
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