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RichardErkhov/
rwitz2_-_go-bruins-v2.1-gguf

Name: rwitz2_-_go-bruins-v2.1-gguf
Availability: InStock

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gguf

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go-bruins-v2.1 - GGUF

Model creator: https://huggingface.co/rwitz2/
Original model: https://huggingface.co/rwitz2/go-bruins-v2.1/

Name	Quant method	Size
go-bruins-v2.1.Q2_K.gguf	Q2_K	2.53GB
go-bruins-v2.1.IQ3_XS.gguf	IQ3_XS	2.81GB
go-bruins-v2.1.IQ3_S.gguf	IQ3_S	2.96GB
go-bruins-v2.1.Q3_K_S.gguf	Q3_K_S	2.95GB
go-bruins-v2.1.IQ3_M.gguf	IQ3_M	3.06GB
go-bruins-v2.1.Q3_K.gguf	Q3_K	3.28GB
go-bruins-v2.1.Q3_K_M.gguf	Q3_K_M	3.28GB
go-bruins-v2.1.Q3_K_L.gguf	Q3_K_L	3.56GB
go-bruins-v2.1.IQ4_XS.gguf	IQ4_XS	3.67GB
go-bruins-v2.1.Q4_0.gguf	Q4_0	3.83GB
go-bruins-v2.1.IQ4_NL.gguf	IQ4_NL	3.87GB
go-bruins-v2.1.Q4_K_S.gguf	Q4_K_S	3.86GB
go-bruins-v2.1.Q4_K.gguf	Q4_K	4.07GB
go-bruins-v2.1.Q4_K_M.gguf	Q4_K_M	4.07GB
go-bruins-v2.1.Q4_1.gguf	Q4_1	4.24GB
go-bruins-v2.1.Q5_0.gguf	Q5_0	4.65GB
go-bruins-v2.1.Q5_K_S.gguf	Q5_K_S	4.65GB
go-bruins-v2.1.Q5_K.gguf	Q5_K	4.78GB
go-bruins-v2.1.Q5_K_M.gguf	Q5_K_M	4.78GB
go-bruins-v2.1.Q5_1.gguf	Q5_1	5.07GB
go-bruins-v2.1.Q6_K.gguf	Q6_K	5.53GB
go-bruins-v2.1.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: cc-by-nc-4.0 language:

en pipeline_tag: text-generation

Merge:

slices:
  - sources:
      - model: viethq188/LeoScorpius-7B-Chat-DPO
        layer_range: [0, 32]
      - model: GreenNode/GreenNodeLM-7B-v1olet
        layer_range: [0, 32]
merge_method: slerp
base_model: viethq188/LeoScorpius-7B-Chat-DPO
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
dtype: float16

Go Bruins V2.1 - A Fine-tuned Language Model

Updates

Overview

Go Bruins-V2 is a language model fine-tuned on the rwitz/go-bruins architecture. It's designed to push the boundaries of NLP applications, offering unparalleled performance in generating human-like text.

Model Details

Developer: Ryan Witzman
Base Model: rwitz/go-bruins
Fine-tuning Method: Direct Preference Optimization (DPO)
Training Steps: 642
Language: English
License: MIT

Capabilities

Go Bruins excels in a variety of NLP tasks, including but not limited to:

Text generation
Language understanding
Sentiment analysis

Usage

Warning: This model may output NSFW or illegal content. Use with caution and at your own risk.

For Direct Use:

python

from transformers import pipeline

model_name = "rwitz/go-bruins-v2"
inference_pipeline = pipeline('text-generation', model=model_name)

input_text = "Your input text goes here"
output = inference_pipeline(input_text)

print(output)

Not Recommended For:

Illegal activities
Harassment
Professional advice or crisis situations

Training and Evaluation

Trained on a dataset from athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW, Go Bruins V2 has shown promising improvements over its predecessor, Go Bruins.

Evaluations

Metric	Average	Arc Challenge	Hella Swag	MMLU	Truthful Q&A	Winogrande	GSM8k
Score	72.07	69.8	87.05	64.75	59.7	81.45	69.67

Note: The original MMLU evaluation has been corrected to include 5-shot data rather than 1-shot data.

Contact

For any inquiries or feedback, reach out to Ryan Witzman on Discord: rwitz_.

Citations

@misc{unacybertron7b,
  title={Cybertron: Uniform Neural Alignment}, 
  author={Xavier Murias},
  year={2023},
  publisher = {HuggingFace},
  journal = {HuggingFace repository},
  howpublished = {\url{https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16}},
}

This model card was created with care by Ryan Witzman. rewrite this model card for new version called go-bruins-v2 that is finetuned on dpo on the original go-bruins model on athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW

RichardErkhov/rwitz2_-_go-bruins-v2.1-gguf