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---
license: apache-2.0
tags:
- finetuned
- quantized
- 4-bit
- gptq
- transformers
- safetensors
- llama
- text-generation
- dataset:ai2_arc
- dataset:unalignment/spicy-3.1
- dataset:codeparrot/apps
- dataset:facebook/belebele
- dataset:boolq
- dataset:jondurbin/cinematika-v0.1
- dataset:drop
- dataset:lmsys/lmsys-chat-1m
- dataset:TIGER-Lab/MathInstruct
- dataset:cais/mmlu
- dataset:Muennighoff/natural-instructions
- dataset:openbookqa
- dataset:piqa
- dataset:Vezora/Tested-22k-Python-Alpaca
- dataset:cakiki/rosetta-code
- dataset:Open-Orca/SlimOrca
- dataset:spider
- dataset:squad_v2
- dataset:migtissera/Synthia-v1.3
- dataset:datasets/winogrande
- dataset:nvidia/HelpSteer
- dataset:Intel/orca_dpo_pairs
- dataset:unalignment/toxic-dpo-v0.1
- dataset:jondurbin/truthy-dpo-v0.1
- dataset:allenai/ultrafeedback_binarized_cleaned
- dataset:Squish42/bluemoon-fandom-1-1-rp-cleaned
- dataset:LDJnr/Capybara
- dataset:JULIELab/EmoBank
- dataset:kingbri/PIPPA-shareGPT
- license:other
- autotrain_compatible
- endpoints_compatible
- text-generation-inference
- region:us
- has_space
model_name: UNA-34Beagles-32K-bf16-v1-GPTQ
base_model: one-man-army/UNA-34Beagles-32K-bf16-v1
inference: false
model_creator: one-man-army
pipeline_tag: text-generation
quantized_by: MaziyarPanahi
model-index:
- name: UNA-34Beagles-32K-bf16-v1-GPTQ
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: 26.11
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ
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: 26.29
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ
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: 24.43
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ
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: 47.27
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ
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: 50.83
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ
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: 0.0
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ
name: Open LLM Leaderboard
---
# Description
[MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ](https://huggingface.co/MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ) is a quantized (GPTQ) version of [one-man-army/UNA-34Beagles-32K-bf16-v1](https://huggingface.co/one-man-army/UNA-34Beagles-32K-bf16-v1)
## How to use
### Install the necessary packages
```
pip install --upgrade accelerate auto-gptq transformers
```
### Example Python code
```python
from transformers import AutoTokenizer, pipeline
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
import torch
model_id = "MaziyarPanahi/UNA-34Beagles-32K-bf16-v1-GPTQ"
quantize_config = BaseQuantizeConfig(
bits=4,
group_size=128,
desc_act=False
)
model = AutoGPTQForCausalLM.from_quantized(
model_id,
use_safetensors=True,
device="cuda:0",
quantize_config=quantize_config)
tokenizer = AutoTokenizer.from_pretrained(model_id)
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
max_new_tokens=512,
temperature=0.7,
top_p=0.95,
repetition_penalty=1.1
)
outputs = pipe("What is a large language model?")
print(outputs[0]["generated_text"])
```
# [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_MaziyarPanahi__UNA-34Beagles-32K-bf16-v1-GPTQ)
| Metric |Value|
|---------------------------------|----:|
|Avg. |29.15|
|AI2 Reasoning Challenge (25-Shot)|26.11|
|HellaSwag (10-Shot) |26.29|
|MMLU (5-Shot) |24.43|
|TruthfulQA (0-shot) |47.27|
|Winogrande (5-shot) |50.83|
|GSM8k (5-shot) | 0.00|