rombodawg/Open_Gpt4_8x7B_v0.2

Open_Gpt4_v0.2

This is the un-quantized fp16 version for training and merging. If you want the quantized version for inference please refer to the repo bellow:

• https://huggingface.co./rombodawg/Open_Gpt4_8x7B_v0.2_q8_0_gguf

This model is a TIES merger of Mixtral-8x7B-Instruct-v0.1 and bagel-dpo-8x7b-v0.2 with MixtralOrochi8x7B being the Base model.

I was very impressed with MixtralOrochi8x7B performance and multifaceted usecases as it is already a merger of many usefull Mixtral models such as Mixtral instruct, Noromaid-v0.1-mixtral, openbuddy-mixtral and possibly other models that were not named. My goal was to expand the models capabilities and make it even more useful of a model, maybe even competitive with closed source models like Gpt-4. But for that more testing is required. I hope the community can help me determine if its deserving of its name. 😊

This is the second iteration of this model, using better models in the merger to improve performance (hopefully).

Base model:

• https://huggingface.co./smelborp/MixtralOrochi8x7B

Merged models:

• https://huggingface.co./mistralai/Mixtral-8x7B-Instruct-v0.1

• https://huggingface.co./jondurbin/bagel-dpo-8x7b-v0.2

Instruct template: Alpaca

Merger config:

models:
  - model: Mixtral-8x7B-Instruct-v0.1

    parameters:
      density: .5
      weight: 1
  - model: bagel-dpo-8x7b-v0.2
    parameters:
      density: .5
      weight: .7


merge_method: ties
base_model: MixtralOrochi8x7B
parameters:
  normalize: true
  int8_mask: true
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	73.59
AI2 Reasoning Challenge (25-Shot)	68.69
HellaSwag (10-Shot)	86.16
MMLU (5-Shot)	72.07
TruthfulQA (0-shot)	71.92
Winogrande (5-shot)	83.58
GSM8k (5-shot)	59.14