license, datasets, language

license	datasets	language
apache-2.0	guanaco/guanaco	en

# Model Card for Model ID This is a finetuned model of Cerebras 256M model using DataBricksLabs Dolly Framework ## Model Details ### Model Description - 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 [optional]: https://huggingface.co/cerebras/Cerebras-GPT-256M ## 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 almost non-existant. ### Direct Use [More Information Needed] ### Downstream Use [optional] [More Information Needed] ### Out-of-Scope Use [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ### Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results

Summary

Model Examination [optional]

[More Information Needed]

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Hardware Type: [More Information Needed]
• Hours used: [More Information Needed]
• Cloud Provider: [More Information Needed]
• Compute Region: [More Information Needed]
• 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]

BibTeX:

[More Information Needed]

APA:

[More Information Needed]

Glossary [optional]

[More Information Needed]

More Information [optional]

[More Information Needed]

Model Card Authors [optional]

[More Information Needed]

Model Card Contact

[More Information Needed]

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	24.88
ARC (25-shot)	22.87
HellaSwag (10-shot)	28.84
MMLU (5-shot)	26.48
TruthfulQA (0-shot)	39.47
Winogrande (5-shot)	52.25
GSM8K (5-shot)	0.0
DROP (3-shot)	4.27