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penny5-dolphin-einstein-llama3-dare-ties-chatml - GGUF

Name Quant method Size
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q2_K.gguf Q2_K 2.96GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.IQ3_XS.gguf IQ3_XS 3.28GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.IQ3_S.gguf IQ3_S 3.43GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q3_K_S.gguf Q3_K_S 3.41GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.IQ3_M.gguf IQ3_M 3.52GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q3_K.gguf Q3_K 3.74GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q3_K_M.gguf Q3_K_M 3.74GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q3_K_L.gguf Q3_K_L 4.03GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.IQ4_XS.gguf IQ4_XS 4.18GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q4_0.gguf Q4_0 4.34GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.IQ4_NL.gguf IQ4_NL 4.38GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q4_K_S.gguf Q4_K_S 4.37GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q4_K.gguf Q4_K 4.58GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q4_K_M.gguf Q4_K_M 4.58GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q4_1.gguf Q4_1 4.78GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q5_0.gguf Q5_0 5.21GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q5_K_S.gguf Q5_K_S 5.21GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q5_K.gguf Q5_K 5.34GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q5_K_M.gguf Q5_K_M 5.34GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q5_1.gguf Q5_1 5.65GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q6_K.gguf Q6_K 6.14GB
penny5-dolphin-einstein-llama3-dare-ties-chatml.Q8_0.gguf Q8_0 7.95GB

Original model description:

library_name: transformers tags: - llama-factory license: llama3 language: - en

Model Card for Model ID

image/webp

This is a fine tune of a merged model using the DARE TIES merge method using cognitivecomputations/dolphin-2.9-llama3-8b as a base. The following models were included in the merge:

This model should be mostly uncensored out of the box. I personally add a system prompt with the chatml template to guide the model.

Model Details

Quant Q8_0 GGUF

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub.

Training Details

Training Data

[More Information Needed]

Training Procedure

Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

[More Information Needed]

Evaluation

Metric Value
Avg. 66.72
ARC (25-shot) 61.01
HellaSwag (10-shot) 82.50
MMLU (5-shot) 64.48
TruthfulQA (0-shot) 50.73
Winogrande (5-shot) 74.11
GSM8K (5-shot) 67.48

full results here

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: [Nvidia RTX A100]
  • Hours used: [2]
  • Cloud Provider: [RunPod]
  • Compute Region: [Europe]
  • Carbon Emitted: [More Information Needed]

Model Card Authors

[Gianni Sanrochman]

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