README.md

metadata

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
            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

This is Xander Boyce's OmegLLaMA LoRA merged with OpenLLama 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.

This model is very good at NSFW ERP and sexting(For a 3B model). I recommend using this with Faraday.dev if you want ERP or sexting.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

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

Detailed results can be found here

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