RichardErkhov/giannisan_-_penny5-dolphin-einstein-llama3-dare-ties-chatml-gguf
Quantization made by Richard Erkhov.
penny5-dolphin-einstein-llama3-dare-ties-chatml - GGUF
- Model creator: https://huggingface.co/giannisan/
- Original model: https://huggingface.co/giannisan/penny5-dolphin-einstein-llama3-dare-ties-chatml/
Original model description: --- library_name: transformers tags:
- llama-factory license: llama3 language:
- en ---
Model Card for Model ID

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
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub.
- Developed by: Gianni Sanrochman
- Funded by: [Merildo Sanrochman]
- Model type: LLaMA-3
- Language(s) (NLP): [English]
- License: llama3
- Finetuned from model: giannisan/dolphin-einstein-llama3-dare-ties using the PENNY dataset
Training Details
Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
Training Hyperparameters
- Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
Evaluation
full results here
Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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]
