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Edentns_-_DataVortexS-10.7B-dpo-v1.4-gguf
RichardErkhov/Edentns_-_DataVortexS-10.7B-dpo-v1.4-gguf
Edentns_-_DataVortexS-10.7B-dpo-v1.4-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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At a glance
- Access
- Public
- Created
- Jul 30, 2024
- Updated
- Jul 30, 2024
- SHA
- 86a3e11f
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
DataVortexS-10.7B-dpo-v1.4 - GGUF
- Model creator: https://huggingface.co/Edentns/
- Original model: https://huggingface.co/Edentns/DataVortexS-10.7B-dpo-v1.4/
Original model description:
tags: - text-generation license: cc-by-nc-4.0 language: - ko base_model: yanolja/Bookworm-10.7B-v0.4-DPO pipeline_tag: text-generation
DataVortexS-10.7B-dpo-v1.4
<img src="./DataVortex.png" alt="DataVortex" style="height: 8em;">Our Team
| Research & Engineering | Product Management |
|---|---|
| Kwangseok Yang | Seunghyun Choi |
| Jeongwon Choi | Hyoseok Choi |
Model Details
Base Model
yanolja/Bookworm-10.7B-v0.4-DPO
Trained On
- OS: Ubuntu 22.04
- GPU: H100 80GB 4ea
- transformers: v4.36.2
Instruction format
It follows ChatML format.
E.g.
text = """\
<|im_start|>system
당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다.<|im_end|>
<|im_start|>user
대한민국의 수도는 어디야?<|im_end|>
<|im_start|>assistant
대한민국의 수도는 서울입니다.<|im_end|>
<|im_start|>user
서울 인구는 총 몇 명이야?<|im_end|>
<|im_start|>assistant
"""
Model Benchmark
Ko LM Eval Harness
| Task | 0-shot | 5-shot | 10-shot | 50-shot |
|---|---|---|---|---|
| kobest_boolq | 0.757911 | 0.907177 | 0.924496 | 0.605075 |
| kobest_copa | 0.740605 | 0.801886 | 0.831886 | 0.849978 |
| kobest_hellaswag | 0.445176 | 0.454788 | 0.468654 | 0.45218 |
| kobest_sentineg | 0.415445 | 0.95214 | 0.962217 | 0.967254 |
| Average | 0.589784 | 0.778998 | 0.796813 | 0.718622 |
Ko-LLM-Leaderboard
| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
|---|---|---|---|---|---|
| 53.81 | 52.05 | 62.93 | 53.59 | 50.42 | 50.06 |
Implementation Code
This model contains the chat_template instruction format.
You can use the code below.
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.4")
tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.4")
messages = [
{"role": "system", "content": "당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다."},
{"role": "user", "content": "대한민국의 수도는 어디야?"},
{"role": "assistant", "content": "대한민국의 수도는 서울입니다."},
{"role": "user", "content": "서울 인구는 총 몇 명이야?"}
]
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])
License
This model is licensed under the cc-by-nc-4.0. which allows others to share and adapt the model for non-commercial purposes.
<div align="center"> <a href="https://edentns.com/"> <img src="./Logo.png" alt="Logo" style="height: 3em;"> </a> </div>- Created
- Jul 30, 2024
- Updated
- Jul 30, 2024