Instructions to use eagle0504/pretrained_transformer_model_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use eagle0504/pretrained_transformer_model_v1 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://eagle0504/pretrained_transformer_model_v1") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
---
language: en
license: apache-2.0
tags:
- question-answering
- transformer
- educational
datasets:
- custom
metrics:
- accuracy
---
# Model Card for pretrained_transformer_model_v1
## Model Details
This is a Transformer model trained for demonstration purposes. The model was trained using a dataset of question-answer pairs and is designed to understand simple natural language questions.
## Intended Use
This model is intended for educational purposes and demonstrations. It is not suitable for production use or handling sensitive data.
## Limitations
The model may not perform well on out-of-domain questions or complex natural language understanding tasks.
## Training Data
The model was trained on a small dataset of questions and answers created for this demonstration.
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