---
language:
- en
license: apache-2.0
library_name: transformers
datasets:
- yahma/alpaca-cleaned
pipeline_tag: text-generation
model-index:
- name: speechless-mistral-moloras-7b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 59.98
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=uukuguy/speechless-mistral-moloras-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 83.29
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=uukuguy/speechless-mistral-moloras-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.12
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=uukuguy/speechless-mistral-moloras-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 42.15
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=uukuguy/speechless-mistral-moloras-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 78.37
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=uukuguy/speechless-mistral-moloras-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 37.68
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=uukuguy/speechless-mistral-moloras-7b
      name: Open LLM Leaderboard
---

<p><h1> speechless-mistral-moloras-7b </h1></p>

* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/speechless-mistral-moloras-7B-AWQ)
* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/speechless-mistral-moloras-7B-GPTQ)
* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/speechless-mistral-moloras-7B-GGUF)

[4-bit GGUF models for CPU+GPU inference](https://huggingface.co/uukuguy/speechless-mistral-moloras-7b/tree/main/GGUF)

This model is the static version of moloras (Mixture-of-multi-LoRAs) based on the following 6 Mistral-based LoRa modules.

- Intel/neural-chat-7b-v3-1 
- migtissera/SynthIA-7B-v1.3
- jondurbin/airoboros-m-7b-3.1.2
- bhenrym14/mistral-7b-platypus-fp16 
- teknium/CollectiveCognition-v1.1-Mistral-7B 
- uukuguy/speechless-mistral-dolphin-orca-platypus-samantha-7b 

Totally 6 LoRA modules from [speechless-mistral-7b-dare-0.85](https://huggingface.co/speechlessai/speechless-mistral-7b-dare-0.85)

The router of mixture-of-multi-loras enables an automatic assembling of LoRA modules, using a gradientfree approach to obtain the coefficients of LoRA modules and requiring only a handful of inference steps for unseen tasks.




Code: https://github.com/uukuguy/multi_loras?tab=readme-ov-file#mixture-of-multi-loras

## LM-Evaluation-Harness

[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)

| Metric | Value |
| --- | --- |
| ARC | 59.98  |
| HellaSwag | 83.29 |
| MMLU | 64.12 |
| TruthfulQA | 42.15 |
| Winogrande | 78.37 |
| GSM8K | 37.68 |
| Average | 60.93 |


# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_uukuguy__speechless-mistral-moloras-7b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |60.93|
|AI2 Reasoning Challenge (25-Shot)|59.98|
|HellaSwag (10-Shot)              |83.29|
|MMLU (5-Shot)                    |64.12|
|TruthfulQA (0-shot)              |42.15|
|Winogrande (5-shot)              |78.37|
|GSM8k (5-shot)                   |37.68|