Update README.md

README.md

@@ -1,144 +1,148 @@
----
-base_model: unsloth/llama-3-8b-Instruct
-license: llama3
-datasets:
-- LogCreative/latex-pgfplots-instruct
-language:
-- en
-metrics:
-- code_eval
-library_name: peft
-pipeline_tag: text-generation
-tags:
-- code
----
-
-## Usage
-
-This model is saved as [MLC LLM](https://llm.mlc.ai) format.
-View the [installation guide of MLC LLM](https://llm.mlc.ai/docs/install/mlc_llm) for how to install the library.
-Then use the following command to try the model:
-```bash
-mlc_llm chat .
-```
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-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](https://huggingface.co/datasets/LogCreative/latex-pgfplots-instruct) extracted from the documentation of [`pgfplots`](https://github.com/pgf-tikz/pgfplots) LaTeX package.
-
-- **Developed by:** [LogCreative](https://github.com/LogCreative)
-- **Model type:** Text Generation
-- **Language(s) (NLP):** English
-- **License:** Llama 3
-- **Finetuned from model:** [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b)
-
-### Model Sources
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [LogCreative/llama-pgfplots-finetune](https://github.com/LogCreative/llama-pgfplots-finetune)
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-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
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[PGFPlotsEdt](https://github.com/LogCreative/PGFPlotsEdt): A PGFPlots Statistic Graph Interactive Editor.
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-Any use outside the `pgfplots` package could only be of the performance of the base Llama 3 model.
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-This model could not provide sufficient information on other LaTeX packages and could not guarantee the absolute correctness of the generated result.
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-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
-
-<!-- This should link to a Dataset 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. -->
-
-[LogCreative/latex-pgfplots-instruct](https://huggingface.co/datasets/LogCreative/latex-pgfplots-instruct): a datasets contains the instruction and corresponding output related to `pgfplots` and `pgfplotstable` LaTeX packages.
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-This model is finetuned based on the dataset based on [`unsloth`](https://github.com/unslothai/unsloth) library.
-
-#### Training Hyperparameters
-
-- **Training regime:** bf16 mixed precision <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-The evaluation is based on the success compilation rate of the output LaTeX code in the test dataset.
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[LogCreative/latex-pgfplots-instruct](https://huggingface.co/datasets/LogCreative/latex-pgfplots-instruct): the test part of this dataset only contains instructions only related to the `pgfplots` package.
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-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
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-Success compilation rate: $\frac{\text{\#Success compilation}}{\text{\#Total compilation}}\times 100\%$. The uncessful compilation is rather LaTeX failure or the timeout case (compilation time > 20s).
-
-### Results
-
-- 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
-
-<!-- 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](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **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
+---
+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](https://llm.mlc.ai) format.
+View the [installation guide of MLC LLM](https://llm.mlc.ai/docs/install/mlc_llm) for how to install the library.
+Then use the following command to try the model:
+```bash
+mlc_llm chat .
+```
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+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](https://huggingface.co/datasets/LogCreative/latex-pgfplots-instruct) extracted from the documentation of [`pgfplots`](https://github.com/pgf-tikz/pgfplots) LaTeX package.
+
+- **Developed by:** [LogCreative](https://github.com/LogCreative)
+- **Model type:** Text Generation
+- **Language(s) (NLP):** English
+- **License:** Llama 3
+- **Finetuned from model:** [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b)
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [LogCreative/llama-pgfplots-finetune](https://github.com/LogCreative/llama-pgfplots-finetune)
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+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
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[PGFPlotsEdt](https://github.com/LogCreative/PGFPlotsEdt): A PGFPlots Statistic Graph Interactive Editor.
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+Any use outside the `pgfplots` package could only be of the performance of the base Llama 3 model.
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+This model could not provide sufficient information on other LaTeX packages and could not guarantee the absolute correctness of the generated result.
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+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
+
+<!-- This should link to a Dataset 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. -->
+
+[LogCreative/latex-pgfplots-instruct](https://huggingface.co/datasets/LogCreative/latex-pgfplots-instruct): a datasets contains the instruction and corresponding output related to `pgfplots` and `pgfplotstable` LaTeX packages.
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+This model is finetuned based on the dataset based on [`unsloth`](https://github.com/unslothai/unsloth) library.
+
+#### Training Hyperparameters
+
+- **Training regime:** bf16 mixed precision <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+The evaluation is based on the success compilation rate of the output LaTeX code in the test dataset.
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[LogCreative/latex-pgfplots-instruct](https://huggingface.co/datasets/LogCreative/latex-pgfplots-instruct): the test part of this dataset only contains instructions only related to the `pgfplots` package.
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+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
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+Success compilation rate: $\frac{\text{\#Success compilation}}{\text{\#Total compilation}}\times 100\%$. 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
+
+<!-- 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](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **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