Instructions to use paralleldynamix/paralleldynamix-model101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use paralleldynamix/paralleldynamix-model101 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://paralleldynamix/paralleldynamix-model101") - Notebooks
- Google Colab
- Kaggle
metadata
license: gpl-3.0
datasets:
- Open-Orca/OpenOrca
- openchat/openchat_sharegpt4_dataset
- databricks/databricks-dolly-15k
- tiiuae/falcon-refinedweb
- Salesforce/dialogstudio
language:
- en
metrics:
- character
- accuracy
- code_eval
library_name: keras
pipeline_tag: conversational
tags:
- code
- finance
- legal
- text-generation-inference