Llama2-7b-economist

Llama2-7b-economist

Llama2-7b-economist is a state-of-the-art language model with 7 billion parameters, specifically fine-tuned on extensive Macro and Micro Economic theory. It aims to provide data-driven economic insights and predictions.

Model Details

Model Description

Llama2-7b-economist represents the intersection of cutting-edge AI modeling and economic theory. By leveraging a vast parameter space and meticulous fine-tuning, this model seeks to transform the way we approach and understand economic data.

  • Developed by: Collin Heenan
  • Model type: Transformer-based Language Model
  • Language(s): English
  • License: MIT
  • Finetuned from model: Llama2-7b Base Model

Model Sources

  • Repository: [More Information Needed]
  • Demo: [More Information Needed]

Uses

Direct Use

  • Economic predictions based on text inputs.
  • Answering questions related to Macro and Micro Economic theories.
  • Analyzing economic texts and extracting insights.

Downstream Use

  • Potential to be fine-tuned for specific economic tasks, such as economic sentiment analysis or financial forecasting.

Out-of-Scope Use

  • Non-economic related tasks.
  • Predictions that require non-textual data, like graphs or charts.

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Users should ensure they are using Llama2-7b-economist in appropriate economic contexts and be cautious of extrapolating predictions without expert validation.

How to Get Started with the Model

[More Information Needed]

Training Details

Llama2-7b-economist

Training Data

  • Comprehensive Macro and Micro Economic theory datasets.

Training Procedure

Training Hyperparameters

  • Training regime: Training on 1x t4 GPU

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator.

  • Hardware Type: NVIDIA T4 GPU
  • Hours used: [More Information Needed]
  • Cloud Provider: [More Information Needed]
  • Compute Region: [More Information Needed]
  • Carbon Emitted: [More Information Needed]

Technical Specifications

Model Architecture and Objective

Transformer-based architecture with 7 billion parameters, designed to understand and predict economic patterns and insights.

Compute Infrastructure

Hardware

  • 1x t4 GPU

Contact

Downloads last month
23
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Datasets used to train cxllin/Llama2-7b-economist

Collection including cxllin/Llama2-7b-economist