RichardErkhov/acrastt_-_Puma-3B-8bits

Quantization made by Richard Erkhov.

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Puma-3B - bnb 8bits

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

Original model description:

language: - en license: apache-2.0 library_name: transformers datasets: - totally-not-an-llm/sharegpt-hyperfiltered-3k pipeline_tag: text-generation model-index: - name: Puma-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: 41.3 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-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: 71.85 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-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: 27.51 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-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: 38.34 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-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: 66.38 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-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: 0.76 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/Puma-3B name: Open LLM Leaderboard

This is OpenLLaMA 3B V2 finetuned on ShareGPT Hyperfiltered for 1 epochs.

Prompt template:

### HUMAN:
{prompt}

### RESPONSE:
<leave a newline for the model to answer>

GGML quants available here.
GPTQ quants available here.

Note: Don't expect this model to be good, I was just starting out to finetune. So don't roast me please!

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	41.02
ARC (25-shot)	41.3
HellaSwag (10-shot)	71.85
MMLU (5-shot)	27.51
TruthfulQA (0-shot)	38.34
Winogrande (5-shot)	66.38
GSM8K (5-shot)	0.76

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	41.02
AI2 Reasoning Challenge (25-Shot)	41.30
HellaSwag (10-Shot)	71.85
MMLU (5-Shot)	27.51
TruthfulQA (0-shot)	38.34
Winogrande (5-shot)	66.38
GSM8k (5-shot)	0.76