base_model: unsloth/llama-3-8b-Instruct
license: llama3
datasets:
- LogCreative/latex-pgfplots-instruct
language:
- en
metrics:
- code_eval
pipeline_tag: text-generation
tags:
- code
Usage
This model is saved as MLC LLM format. View the installation guide of MLC LLM for how to install the library. Then use the following command to try the model:
mlc_llm chat .
Model Details
Model Description
The model is finetuned from Llama 3 LLM to provide more accurate results on generating LaTeX code of pgfplots
package, which is based on the dataset LogCreative/latex-pgfplots-instruct extracted from the documentation of pgfplots
LaTeX package.
- Developed by: LogCreative
- Model type: Text Generation
- Language(s) (NLP): English
- License: Llama 3
- Finetuned from model: unsloth/llama-3-8b-Instruct
Model Sources
- Repository: LogCreative/llama-pgfplots-finetune
Uses
This model is intended to generate the pgfplots LaTeX code according to the user's prompt.
It is suitable for users who are not familiar with the API provided in the pgfplots
package
or does not want to consult the documentation for achieving the intention.
Direct Use
PGFPlotsEdt: A PGFPlots Statistic Graph Interactive Editor.
Out-of-Scope Use
Any use outside the pgfplots
package could only be of the performance of the base Llama 3 model.
Bias, Risks, and Limitations
This model could not provide sufficient information on other LaTeX packages and could not guarantee the absolute correctness of the generated result.
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
If you can not get the correct result from this model, you may need to consult the original pgfplots
documentation for more information.
Training Details
Training Data
LogCreative/latex-pgfplots-instruct: a datasets contains the instruction and corresponding output related to pgfplots
and pgfplotstable
LaTeX packages.
Training Procedure
This model is finetuned based on the dataset based on unsloth
library.
Training Hyperparameters
- Training regime: bf16 mixed precision
Evaluation
The evaluation is based on the success compilation rate of the output LaTeX code in the test dataset.
Testing Data, Factors & Metrics
Testing Data
LogCreative/latex-pgfplots-instruct: the test part of this dataset only contains instructions only related to the pgfplots
package.
Factors
When testing, the prompt prefix is added to tell the model what role it is and what the requested response format is to only output the code without any explanation.
Metrics
Success compilation rate: The uncessful compilation is rather LaTeX failure or the timeout case (compilation time > 20s).
Results
The test is based upon unquantized model which is in fp16 precision.
- Llama 3: 34%
- This model: 52% (+18%)
Summary
This model is expected to output the LaTeX code output related to the pgfplots
package with less error compared to the baseline Llama 3 model.
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator.
- Hardware Type: Nvidia A100 80G
- Hours used: 1h = 10min training + 50min testing
- Cloud Provider: Private infrastructure
- Carbon Emitted: 0.11kg CO2 eq.
Framework versions
- PEFT 0.11.1
- MLC LLM nightly_cu122-0.1.dev1404
- MLC AI nightly_cu122-0.15.dev404
- Unsloth 2024.6