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# Model Card for Kimiko_13B

<!-- Provide a quick summary of what the model is/does. -->

This is my new Kimiko models, trained with LLaMA2-13B for...purpose

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->



- **Developed by:** nRuaif
- **Model type:** Decoder only
- **License:**  CC BY-NC-SA 
- **Finetuned from model [optional]:** LLaMA 2

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/OpenAccess-AI-Collective/axolotl
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
## 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. -->


### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->

This model is trained on 3k examples of instructions dataset, high quality roleplay, for best result follow this format
```
<<HUMAN>>
How to do abc

<<AIBOT>>
Here is how

Or with system prompting for roleplay

<<SYSTEM>>
A's Persona:
B's Persona:
Scenario:
Add some instruction here on how you want your RP to go.
```


## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

All bias of this model come from LlaMA2 with an exception of NSFW bias.....




## Training Details

### Training Data

<!-- This should link to a Data 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. -->

3000 examples from LIMAERP, LIMA and I sample 1000 good instruction from Airboro

### Training Procedure 

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

Model is trained with 1 L4 from GCP costing a whooping 2.5USD 





#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

3 epochs with 0.0002 lr, full 4096 ctx token, QLoRA

#### Speeds, Sizes, Times [optional]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

It takes 18 hours to train this model with xformers enable

[More Information Needed]







[More Information Needed]

## 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:** L4 with 12CPUs 48gb ram
- **Hours used:** 5
- **Cloud Provider:** GCP
- **Compute Region:** US
- **Carbon Emitted:** 0.5KG