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RichardErkhov/
acrastt_-_OmegLLaMA-3B-gguf

Name: acrastt_-_OmegLLaMA-3B-gguf
Availability: InStock

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gguf

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Quantization made by Richard Erkhov.

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OmegLLaMA-3B - GGUF

Model creator: https://huggingface.co/acrastt/
Original model: https://huggingface.co/acrastt/OmegLLaMA-3B/

Name	Quant method	Size
OmegLLaMA-3B.Q2_K.gguf	Q2_K	1.84GB
OmegLLaMA-3B.IQ3_XS.gguf	IQ3_XS	1.84GB
OmegLLaMA-3B.IQ3_S.gguf	IQ3_S	1.84GB
OmegLLaMA-3B.Q3_K_S.gguf	Q3_K_S	1.84GB
OmegLLaMA-3B.IQ3_M.gguf	IQ3_M	1.92GB
OmegLLaMA-3B.Q3_K.gguf	Q3_K	1.99GB
OmegLLaMA-3B.Q3_K_M.gguf	Q3_K_M	1.99GB
OmegLLaMA-3B.Q3_K_L.gguf	Q3_K_L	2.06GB
OmegLLaMA-3B.IQ4_XS.gguf	IQ4_XS	1.86GB
OmegLLaMA-3B.Q4_0.gguf	Q4_0	1.84GB
OmegLLaMA-3B.IQ4_NL.gguf	IQ4_NL	1.86GB
OmegLLaMA-3B.Q4_K_S.gguf	Q4_K_S	2.24GB
OmegLLaMA-3B.Q4_K.gguf	Q4_K	2.4GB
OmegLLaMA-3B.Q4_K_M.gguf	Q4_K_M	2.4GB
OmegLLaMA-3B.Q4_1.gguf	Q4_1	2.04GB
OmegLLaMA-3B.Q5_0.gguf	Q5_0	2.23GB
OmegLLaMA-3B.Q5_K_S.gguf	Q5_K_S	2.42GB
OmegLLaMA-3B.Q5_K.gguf	Q5_K	2.57GB
OmegLLaMA-3B.Q5_K_M.gguf	Q5_K_M	2.57GB
OmegLLaMA-3B.Q5_1.gguf	Q5_1	2.42GB
OmegLLaMA-3B.Q6_K.gguf	Q6_K	3.39GB
OmegLLaMA-3B.Q8_0.gguf	Q8_0	3.39GB

Original model description:

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

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

RichardErkhov/acrastt_-_OmegLLaMA-3B-gguf

Original model description:

Open LLM Leaderboard Evaluation Results

Open LLM Leaderboard Evaluation Results

RichardErkhov/
acrastt_-_OmegLLaMA-3B-gguf