This is a text generation model based on the OPT-1.3B model from Meta, trained using the Deepspeed library. The model can generate natural and engaging conversational responses given a user input.
A Demo is available here
The model is best at simple Q&A style questions, not open-ended ones like ChatGPT.
Training Details
The base model is OPT-1.3B, a decoder-only transformer with 1.3 billion parameters, pre-trained on a large text corpus using the causal language modeling objective.
The model was trained on a single NVIDIA A100 GPU using the Deepspeed pipeline parallelism and ZeRO optimizer.
Model Details
Number of parameters: 1.3 billion
Number of layers: 24
Number of attention heads: 16
Context size: 2048
Vocabulary size: 50,265
Embedding size: 1280
Feed-forward size: 5120
Dropout rate: 0.1
Usage
You can use this model directly with the Hugging Face pipeline for text generation:
python
1from transformers import pipeline
2generator = pipeline('text-generation', model='DarwinAnim8or/OPT-1.3b-Chat')3generator("Hello, how are you?")
Suggested formatting
The training data uses the following format:
Human: <question>
Assistant: <answer>
It is recommended to follow the same format as closely as possible for the best results.
We do intend on creating another model that is trained on the openassistant dataset in the future.
License
This model is licensed under the OPT-175B license, which is a non-commercial research license. Please read the full license terms before using this model.
Ethical Considerations
This model is intended for research purposes only and should not be used for any malicious or harmful applications. The model may generate offensive or inappropriate content that does not reflect the views or opinions of the authors or Microsoft. Users are responsible for ensuring that the generated content complies with ethical and legal standards.
