### Description
Do you miss the vibes of the early 2000s? Yearn for the nostalgia of internet religious arguments? Then this model is for you!

This was trained on a scrape of Yahoo! Answers from 2007 and received no filtering save for basic sanity checks.

This is not intended for serious use but I think it's charming in a way.

### Prompt format: 
Pygmalion / Metharme

The prompt should start with the cursor on the same line directly after "<|model|>" with no space. The following are all valid formats and can be extended to as many rounds as desired.
```
<|system|>system message here<|user|>user message here<|model|>
```
```
<|system|>system message here<|user|>user message here<|model|>model message<|user|>user message here<|model|>
```
```
<|system|>system message here<|model|>
```
```
<|system|>system message here<|model|>model message<|user|>user message here<|model|>
```

# Some quick and  dirty training details:
- [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="150" height="24"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
- Sequence length: 2048
- Training time: 32 hours
- Hardware: 1x RTX 4080
- Training type: QLoRA
- PEFT R/A: 32/32
{"language": ["en"], "license": "apache-2.0", "datasets": ["PocketDoc/Retro-YahooAnswers"], "pipeline_tag": "question-answering", "base_model": "mistralai/Mistral-7B-v0.1"}
transformers pytorch mistral text-generation question-answering en dataset:PocketDoc/Retro-YahooAnswers base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us