CoolFace
Modelpublic

RichardErkhov/beberik_-_Nyxene-v3-11B-8bits

sourceHugging Faceupdated 2y agoView on Hugging Face
0likes18downloads
Model Card

Quantization made by Richard Erkhov.

Github

Discord

Request more models

Nyxene-v3-11B - bnb 8bits

  • —Model creator: https://huggingface.co/beberik/
  • —Original model: https://huggingface.co/beberik/Nyxene-v3-11B/

Original model description: --- license: cc-by-nc-4.0 tags:

  • —merge model-index:
  • —name: Nyxene-v3-11B results:
  • —task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2arc config: ARC-Challenge split: test args: numfew_shot: 25 metrics:
  • —type: accnorm value: 69.62 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=beberik/Nyxene-v3-11B name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: numfewshot: 10 metrics:
  • —type: accnorm value: 85.33 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=beberik/Nyxene-v3-11B name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: numfewshot: 5 metrics:
  • —type: acc value: 64.75 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=beberik/Nyxene-v3-11B name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthfulqa config: multiplechoice split: validation args: numfewshot: 0 metrics:
  • —type: mc2 value: 60.91 source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=beberik/Nyxene-v3-11B name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winograndexl split: validation args: numfew_shot: 5 metrics:
  • —type: acc value: 80.19 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=beberik/Nyxene-v3-11B name: Open LLM Leaderboard
  • —task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: numfewshot: 5 metrics:
  • —type: acc value: 63.53 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=beberik/Nyxene-v3-11B name: Open LLM Leaderboard ---

Description

This repo contains bf16 files of Nyxene-v1-11B. Just new version with some new things.

Model used

Prompt template

Just use chatml.

The secret sauce

go-bruins-loyal-piano-11B :

slices:
  - sources:
    - model: rwitz/go-bruins-v2
      layer_range: [0, 24]
  - sources:
    - model: chargoddard/loyal-piano-m7-cdpo
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16

neural-marcoroni-11B :

slices:
  - sources:
    - model: AIDC-ai-business/Marcoroni-7B-v3
      layer_range: [0, 24]
  - sources:
    - model: Intel/neural-chat-7b-v3-3-Slerp
      layer_range: [8, 32]

merge_method: passthrough
dtype: bfloat16

Nyxene-11B :

slices:
  - sources:
      - model: "./go-bruins-loyal-piano-11B"
        layer_range: [0, 48]
      - model: "./neural-marcoroni-11B"
        layer_range: [0, 48]
merge_method: slerp
base_model: "./go-bruins-loyal-piano-11B"
parameters:
  t:
    - filter: lm_head 
      value: [0.5]
    - filter: embed_tokens
      value: [0.75]
    - filter: self_attn
      value: [0.75, 0.25]
    - filter: mlp
      value:  [0.25, 0.75]
    - filter: layernorm
      value: [0.5, 0.5]
    - filter: modelnorm
      value: [0.5]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16

I use mergekit for all the manipulation told here.

Thanks to the Undi95 for the original 11B mistral merge recipe.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

MetricValue
Avg.70.72
AI2 Reasoning Challenge (25-Shot)69.62
HellaSwag (10-Shot)85.33
MMLU (5-Shot)64.75
TruthfulQA (0-shot)60.91
Winogrande (5-shot)80.19
GSM8k (5-shot)63.53