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Edentns_-_DataVortexS-10.7B-v1.0-gguf
RichardErkhov/Edentns_-_DataVortexS-10.7B-v1.0-gguf
Edentns_-_DataVortexS-10.7B-v1.0-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 27, 2024
- Updated
- Jul 27, 2024
- SHA
- de6e3082
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
DataVortexS-10.7B-v1.0 - GGUF
- Model creator: https://huggingface.co/Edentns/
- Original model: https://huggingface.co/Edentns/DataVortexS-10.7B-v1.0/
| Name | Quant method | Size |
|---|---|---|
| DataVortexS-10.7B-v1.0.Q2_K.gguf | Q2_K | 3.73GB |
| DataVortexS-10.7B-v1.0.IQ3_XS.gguf | IQ3_XS | 4.14GB |
| DataVortexS-10.7B-v1.0.IQ3_S.gguf | IQ3_S | 4.37GB |
| DataVortexS-10.7B-v1.0.Q3_K_S.gguf | Q3_K_S | 4.34GB |
| DataVortexS-10.7B-v1.0.IQ3_M.gguf | IQ3_M | 4.51GB |
| DataVortexS-10.7B-v1.0.Q3_K.gguf | Q3_K | 4.84GB |
| DataVortexS-10.7B-v1.0.Q3_K_M.gguf | Q3_K_M | 4.84GB |
| DataVortexS-10.7B-v1.0.Q3_K_L.gguf | Q3_K_L | 5.26GB |
| DataVortexS-10.7B-v1.0.IQ4_XS.gguf | IQ4_XS | 5.43GB |
| DataVortexS-10.7B-v1.0.Q4_0.gguf | Q4_0 | 5.66GB |
| DataVortexS-10.7B-v1.0.IQ4_NL.gguf | IQ4_NL | 5.72GB |
| DataVortexS-10.7B-v1.0.Q4_K_S.gguf | Q4_K_S | 5.7GB |
| DataVortexS-10.7B-v1.0.Q4_K.gguf | Q4_K | 6.02GB |
| DataVortexS-10.7B-v1.0.Q4_K_M.gguf | Q4_K_M | 6.02GB |
| DataVortexS-10.7B-v1.0.Q4_1.gguf | Q4_1 | 6.27GB |
| DataVortexS-10.7B-v1.0.Q5_0.gguf | Q5_0 | 6.89GB |
| DataVortexS-10.7B-v1.0.Q5_K_S.gguf | Q5_K_S | 6.89GB |
| DataVortexS-10.7B-v1.0.Q5_K.gguf | Q5_K | 7.08GB |
| DataVortexS-10.7B-v1.0.Q5_K_M.gguf | Q5_K_M | 7.08GB |
| DataVortexS-10.7B-v1.0.Q5_1.gguf | Q5_1 | 7.51GB |
| DataVortexS-10.7B-v1.0.Q6_K.gguf | Q6_K | 8.2GB |
| DataVortexS-10.7B-v1.0.Q8_0.gguf | Q8_0 | 10.62GB |
Original model description:
tags: - text-generation license: cc-by-nc-sa-4.0 language: - ko base_model: megastudy/M-SOLAR-10.7B-v1.3 pipeline_tag: text-generation
DataVortexS-10.7B-v1.0
<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
Trained On
- OS: Ubuntu 20.04
- GPU: H100 80GB 4ea
- transformers: v4.36.2
Instruction format
It follows Alpaca format.
E.g.
text = """\
### System:
당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다.
### User:
대한민국의 수도는 어디야?
### Assistant:
대한민국의 수도는 서울입니다.
### User:
서울 인구는 총 몇 명이야?
"""
Model Benchmark
Ko LM Eval Harness
| Task | 0-shot | 5-shot | 10-shot | 50-shot |
|---|---|---|---|---|
| kobest_boolq | 0.334282 | 0.334282 | 0.334282 | 0.769923 |
| kobest_copa | 0.480501 | 0.475746 | 0.46338 | 0.475528 |
| kobest_hellaswag | 0.225818 | 0.240596 | 0.234316 | 0.449779 |
| kobest_sentineg | 0.33165 | 0.386189 | 0.366913 | 0.360296 |
| Average | 0.34306275 | 0.35920325 | 0.34972275 | 0.5138815 |
Ko-LLM-Leaderboard
| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
|---|---|---|---|---|---|
| 40.75 | 49.06 | 25.66 | 53.63 | 45.76 | 29.63 |
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-v1.0")
tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-v1.0")
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
The model is licensed under the cc-by-nc-sa-4.0 license, which allows others to copy, modify, and share the work non-commercially, as long as they give appropriate credit and distribute any derivative works under the same license.
<div align="center"> <a href="https://edentns.com/"> <img src="./Logo.png" alt="Logo" style="height: 3em;"> </a> </div>- Created
- Jul 27, 2024
- Updated
- Jul 27, 2024