metadata

language:
  - ko
library_name: transformers
pipeline_tag: text-generation
license: cc-by-nc-4.0

Synatra-7B-Instruct-v0.2

Made by StableFluffy

Contact

Discord : is.maywell

Telegram : AlzarTakkarsen

License

This model is strictly non-commercial (cc-by-nc-4.0) use only which takes priority over the LLAMA 2 COMMUNITY LICENSE AGREEMENT. The "Model" is completely free (ie. base model, derivates, merges/mixes) to use for non-commercial purposes as long as the the included cc-by-nc-4.0 license in any parent repository, and the non-commercial use statute remains, regardless of other models' licences. The licence can be changed after new model released. If you are to use this model for commercial purpose, Contact me.

Model Details

Base Model
mistralai/Mistral-7B-Instruct-v0.1

Trained On
A6000 48GB * 8

TODO

RP 기반 튜닝 모델 제작
데이터셋 정제
언어 이해능력 개선
상식 보완
토크나이저 변경

Instruction format

In order to leverage instruction fine-tuning, your prompt should be surrounded by [INST] and [/INST] tokens. The very first instruction should begin with a begin of sentence id. The next instructions should not. The assistant generation will be ended by the end-of-sentence token id.

E.g.

text = "<s>[INST] 아이작 뉴턴의 업적을 알려줘. [/INST]"

Model Benchmark

Ko-LLM-Leaderboard

| Model | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | Avg | --- | --- | --- | --- | --- | --- | kyujinpy/KoT-platypus2-13B(No.1 at 10-12) | 43.69 | 53.05 | 42.29 | 43.34 | 65.38 | 49.55 | Synatra-V0.1-7B-Instruct | 39.32 | 41.72 | 49.28 | 43.27 | 43.75 | 43.47 | Synatra-7B-Instruct-v0.2 | 41.81 | 49.35 | 43.99 | 45.77 | 42.96 | 44.78

MMLU에서는 우세하나 Ko-CommonGen V2 에서 크게 약한 모습을 보임.

Implementation Code

Since, chat_template already contains insturction format above. You can use the code below.

from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained("maywell/Synatra-V0.1-7B")
tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-V0.1-7B")

messages = [
    {"role": "user", "content": "What is your favourite condiment?"},
]

encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")

model_inputs = encodeds.to(device)
model.to(device)

generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])

If you run it on oobabooga your prompt would look like this.

[INST] 링컨에 대해서 알려줘. [/INST]

Readme format: beomi/llama-2-ko-7b