metadata
language:
- en
license: cc-by-nc-sa-4.0
library_name: transformers
datasets:
- garage-bAInd/Open-Platypus
pipeline_tag: text-generation
model-index:
- name: PlatYi-34B-Llama-Q-v2
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: 61.09
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/PlatYi-34B-Llama-Q-v2
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: 85.09
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/PlatYi-34B-Llama-Q-v2
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: 76.59
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/PlatYi-34B-Llama-Q-v2
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: 52.65
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/PlatYi-34B-Llama-Q-v2
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: 82.79
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/PlatYi-34B-Llama-Q-v2
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: 49.05
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kyujinpy/PlatYi-34B-Llama-Q-v2
name: Open LLM Leaderboard
PlatYi-34B-Llama-Q-v2
Model Details
Model Developers Kyujin Han (kyujinpy)
Input Models input text only.
Output Models generate text only.
Model Architecture
PlatYi-34B-Llama-Q-v2 is an auto-regressive language model based on the Yi-34B transformer architecture.
Blog Link
Blog: [Coming soon...]
Github: [Coming soon...]
Base Model
chargoddard/Yi-34B-Llama
Training Dataset
garage-bAInd/Open-Platypus.
Fix some bugs
- Before model, there is some mistakes.
- I modified the templates and warmup_steps.
Notice
While training, I used Q-LoRA. The lora_r values is 64.
Model Benchmark
Open leaderboard
- Follow up as link.
Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
---|---|---|---|---|---|---|---|
PlatYi-34B-Llama-Q-v2 | 67.88 | 61.09 | 85.09 | 76.59 | 52.65 | 82.79 | 49.05 |
PlatYi-34B-Llama-Q | 71.13 | 65.70 | 85.22 | 78.78 | 53.64 | 83.03 | 60.42 |
PlatYi-34B-Llama | 68.37 | 67.83 | 85.35 | 78.26 | 53.46 | 82.87 | 42.46 |
Yi-34B-Llama | 70.95 | 64.59 | 85.63 | 76.31 | 55.60 | 82.79 | 60.80 |
Yi-34B | 69.42 | 64.59 | 85.69 | 76.35 | 56.23 | 83.03 | 50.64 |
Implementation Code
### KO-Platypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
repo = "kyujinpy/PlatYi-34B-Llama-Q-v2"
OpenOrca = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float16,
device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 67.88 |
AI2 Reasoning Challenge (25-Shot) | 61.09 |
HellaSwag (10-Shot) | 85.09 |
MMLU (5-Shot) | 76.59 |
TruthfulQA (0-shot) | 52.65 |
Winogrande (5-shot) | 82.79 |
GSM8k (5-shot) | 49.05 |