metadata

license: apache-2.0
datasets:
  - elyza/elyza-tasks-100-TV_0.jsonl
language:
  - ja
base_model:
  - llm-jp/llm-jp-3-13b

Model Card for Model ID

This modelcard aims to be a base template for new models. It has been generated using this raw template.

Model Details

Model Description

Developed by: ktabuchi
Model type: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

Repository: ktabuchi

Uses

For Academic lessons of Matsuo-LLM Lectures

Direct Use

Out-of-Scope Use

Bias, Risks, and Limitations

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

https://liat-aip.sakura.ne.jp/wp/llmのための日本語インストラクションデータ作成/llmのための日本語インストラクションデータ-公開/

[More Information Needed]

Training Procedure

Training Hyperparameters

Training regime: [More Information Needed]

Evaluation

Testing Data, Factors & Metrics

Testing Data

elyza-tasks-100-TV_0.jsonl

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Summary

Environmental Impact

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

Hardware Type:
Hours used: 10
Cloud Provider: Google Colab
Compute Region: A100
Carbon Emitted: [More Information Needed]

Model Architecture and Objective

For Academic Use

Compute Infrastructure

[More Information Needed]

Hardware

[More Information Needed]

Software

[More Information Needed]

BibTeX:

[More Information Needed]

APA:

[More Information Needed]

Model Card Contact

[More Information Needed]