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---
language:
- en
license: apache-2.0
library_name: transformers
tags:
- not-for-all-audiences
datasets:
- anon8231489123/Omegle_logs_dataset
pipeline_tag: text-generation
model-index:
- name: OmegLLaMA-3B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 40.36
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/OmegLLaMA-3B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 66.13
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/OmegLLaMA-3B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 28.0
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/OmegLLaMA-3B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 33.31
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/OmegLLaMA-3B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 61.64
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/OmegLLaMA-3B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 0.23
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/OmegLLaMA-3B
name: Open LLM Leaderboard
---
<a href="https://www.buymeacoffee.com/acrastt" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>
This is [Xander Boyce](https://huggingface.co/takeraparterer)'s [OmegLLaMA LoRA](https://huggingface.co/takeraparterer/Omegllama) merged with [OpenLLama 3B](https://huggingface.co/openlm-research/open_llama_3b).
Prompt format:
```
Interests: {interests}
Conversation:
You: {prompt}
Stranger:
```
For multiple interests, seperate them with space. Repeat You and Stranger for multi-turn conversations, which means Interests and Conversation are technically part of the system prompt.
GGUF quantizations available [here](https://huggingface.co/maddes8cht/acrastt-OmegLLaMA-3B-gguf).
This model is very good at NSFW ERP and sexting(For a 3B model). I recommend using this with [Faraday.dev](https://faraday.dev/) if you want ERP or sexting.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_acrastt__OmegLLaMA-3B)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 38.28 |
| ARC (25-shot) | 40.36 |
| HellaSwag (10-shot) | 66.13 |
| MMLU (5-shot) | 28.0 |
| TruthfulQA (0-shot) | 33.31 |
| Winogrande (5-shot) | 61.64 |
| GSM8K (5-shot) | 0.23 |
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_acrastt__OmegLLaMA-3B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |38.28|
|AI2 Reasoning Challenge (25-Shot)|40.36|
|HellaSwag (10-Shot) |66.13|
|MMLU (5-Shot) |28.00|
|TruthfulQA (0-shot) |33.31|
|Winogrande (5-shot) |61.64|
|GSM8k (5-shot) | 0.23|
|