---
library_name: transformers
license: llama3.1
datasets:
- QuasarResearch/apollo-preview-v0.4
language:
- en
pipeline_tag: text-generation
tags:
- not-for-all-audiences
---

# Model Card for Locutusque/Apollo-0.4-Llama-3.1-8B

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



## Model Details

### Model Description

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Fine-tuned Llama-3.1-8B on QuasarResearch/apollo-preview-v0.4. Results in a decent roleplaying language model, that isn't dumb.

- **Developed by:** Locutusque
- **Model type:** Llama3.1
- **Language(s) (NLP):** English
- **License:** Llama 3.1 Community License Agreement

### Model Sources [optional]

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- **Demo:** https://huggingface.co/spaces/Locutusque/Locutusque-Models
### Direct Use

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

RP/ERP, instruction following, conversation, etc


## Bias, Risks, and Limitations

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This model is completely uncensored - use at your own risk.

### 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. More information needed for further recommendations.


## Training Details

### Training Data

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[QuasarResearch/apollo-preview-v0.4](https://huggingface.co/datasets/QuasarResearch/apollo-preview-v0.4)



#### Training Hyperparameters

- **Training regime:** bf16 non-mixed precision

## Evaluation

|              Tasks              |Version|Filter|n-shot|     Metric      |   | Value  |   |Stderr|
|---------------------------------|------:|------|-----:|-----------------|---|-------:|---|-----:|
|agieval_nous                     |    0.0|none  |      |acc_norm         |↑  |  0.3833|±  |0.0094|
| - agieval_aqua_rat              |    1.0|none  |     0|acc              |↑  |  0.2598|±  |0.0276|
|                                 |       |none  |     0|acc_norm         |↑  |  0.2323|±  |0.0265|
| - agieval_logiqa_en             |    1.0|none  |     0|acc              |↑  |  0.3825|±  |0.0191|
|                                 |       |none  |     0|acc_norm         |↑  |  0.3856|±  |0.0191|
| - agieval_lsat_ar               |    1.0|none  |     0|acc              |↑  |  0.1913|±  |0.0260|
|                                 |       |none  |     0|acc_norm         |↑  |  0.1826|±  |0.0255|
| - agieval_lsat_lr               |    1.0|none  |     0|acc              |↑  |  0.4216|±  |0.0219|
|                                 |       |none  |     0|acc_norm         |↑  |  0.4216|±  |0.0219|
| - agieval_lsat_rc               |    1.0|none  |     0|acc              |↑  |  0.5613|±  |0.0303|
|                                 |       |none  |     0|acc_norm         |↑  |  0.5056|±  |0.0305|
| - agieval_sat_en                |    1.0|none  |     0|acc              |↑  |  0.6553|±  |0.0332|
|                                 |       |none  |     0|acc_norm         |↑  |  0.6068|±  |0.0341|
| - agieval_sat_en_without_passage|    1.0|none  |     0|acc              |↑  |  0.3835|±  |0.0340|
|                                 |       |none  |     0|acc_norm         |↑  |  0.3738|±  |0.0338|
| - agieval_sat_math              |    1.0|none  |     0|acc              |↑  |  0.4136|±  |0.0333|
|                                 |       |none  |     0|acc_norm         |↑  |  0.3227|±  |0.0316|
|arc_challenge                    |    1.0|none  |     0|acc              |↑  |  0.5179|±  |0.0146|
|                                 |       |none  |     0|acc_norm         |↑  |  0.5580|±  |0.0145|
|eq_bench                         |    2.1|none  |     0|eqbench          |↑  | 63.1277|±  |2.3905|
|                                 |       |none  |     0|percent_parseable|↑  |100.0000|±  |0.0000|
|truthfulqa_mc2                   |    2.0|none  |     0|acc              |↑  |  0.5310|±  |0.0150|