README.md

metadata

language:
  - en
datasets:
  - kyujinpy/Open-platypus-Commercial
library_name: transformers
pipeline_tag: text-generation
license: cc-by-nc-sa-4.0

SOLAR-Platypus-10.7B-v1

Model Details

Model Developers Kyujin Han (kyujinpy)

Input Models input text only.

Output Models generate text only.

Model Architecture
SOLAR-Platypus-10.7B-v1 is an auto-regressive language model based on the Llama2 architecture.

Base Model
upstage/SOLAR-10.7B-v1.0

Training Dataset
kyujinpy/Open-platypus-Commercial.

Notice

While training, I used LoRA.
The lora_r values is 16.

Q-LoRA config

• LoRA_r: 16
• LoRA_alpha: 16
• LoRA_dropout: 0.05
• LoRA_target_modules: [gate_proj, up_proj, down_proj]

Prompt

• Alpaca template.

Model Benchmark

Open leaderboard

• Follow up as link.

Model	Average	ARC	HellaSwag	MMLU	TruthfulQA	Winogrande	GSM8K
SOLAR-Platypus-10.7B-v1	NaN	NaN	NaN	NaN	NaN	NaN	NaN
SOLAR-Platypus-10.7B-v2	NaN	NaN	NaN	NaN	NaN	NaN	NaN
upstage/SOLAR-10.7B-v1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Implementation Code

### KO-Platypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "kyujinpy/SOLAR-Platypus-10.7B-v1"
OpenOrca = AutoModelForCausalLM.from_pretrained(
        repo,
        return_dict=True,
        torch_dtype=torch.float16,
        device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)

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