Model Card for Cerebras 2.7b Dollyfied.
This is a finetuned model of Cerebras 2.7b model. using DataBricksLabs Dolly Framework
Model Details
Model Description
This is a finetuned version of cerebras' 2.7Billion paramater model that has been trained to follow instructions.
It was accomplished using DataBricks Dolly training tools, and was trained for 2 epochs.
- Developed by: Finetuned by Corianas (me) using open source tools
- Shared by [optional]: [More Information Needed]
- Model type: [More Information Needed]
- Language(s) (NLP): EN
- License: cc-by-nc-4.0
- Finetuned from model: https://huggingface.co/cerebras/Cerebras-GPT-111m
- Finetuned using: https://www.databricks.com/blog/2023/03/24/hello-dolly-democratizing-magic-chatgpt-open-models.html
Uses
This is a simple GPT chatbot that has been finetuned to understand instructions. Its knowledge about facts about the world is should be considered suspect at best.
Direct Use
If you have a use you put it to, Please let me know.
[More Information Needed]
Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
Out-of-Scope Use
Any form of use where any form of accuracy is needed. FOR THE LOVE OF GOD DO NOT FOLLOW MEDICAL ADVICE FROM THIS. or financial advice.
[More Information Needed]
Bias, Risks, and Limitations
Limitations... Yes, I am sure there are so so many.
[More Information Needed]
How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
Training Details
Training Data
<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
Testing Data, Factors & Metrics
Testing Data
<!-- This should link to a Data Card if possible. -->
[More Information Needed]
Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
Results
[More Information Needed]
Summary
Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: 8xA100s (accomplished while I was downloading the model I was actually training.)
- Minutes used: 25
- Cloud Provider: LambdaGPU
- Compute Region: USA
- Carbon Emitted: [More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
[More Information Needed]
Compute Infrastructure
[More Information Needed]
Hardware
[More Information Needed]
Software
[More Information Needed]
Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
BibTeX:
[More Information Needed]
APA:
[More Information Needed]
Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
More Information [optional]
[More Information Needed]
Model Card Authors [optional]
[More Information Needed]
Model Card Contact
[More Information Needed]