metadata
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
speechless-mistral-moloras-7b
- AWQ model(s) for GPU inference.
- GPTQ models for GPU inference, with multiple quantisation parameter options.
- 2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference
4-bit GGUF models for CPU+GPU inference
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
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
| 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
Detailed results can be found here
| 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 |