|
Quantization made by Richard Erkhov. |
|
|
|
[Github](https://github.com/RichardErkhov) |
|
|
|
[Discord](https://discord.gg/pvy7H8DZMG) |
|
|
|
[Request more models](https://github.com/RichardErkhov/quant_request) |
|
|
|
|
|
multimaster-7b - GGUF |
|
- Model creator: https://huggingface.co/ibivibiv/ |
|
- Original model: https://huggingface.co/ibivibiv/multimaster-7b/ |
|
|
|
|
|
| Name | Quant method | Size | |
|
| ---- | ---- | ---- | |
|
| [multimaster-7b.Q2_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q2_K.gguf) | Q2_K | 2.53GB | |
|
| [multimaster-7b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.IQ3_XS.gguf) | IQ3_XS | 2.81GB | |
|
| [multimaster-7b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.IQ3_S.gguf) | IQ3_S | 2.96GB | |
|
| [multimaster-7b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q3_K_S.gguf) | Q3_K_S | 2.95GB | |
|
| [multimaster-7b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.IQ3_M.gguf) | IQ3_M | 3.06GB | |
|
| [multimaster-7b.Q3_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q3_K.gguf) | Q3_K | 3.28GB | |
|
| [multimaster-7b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q3_K_M.gguf) | Q3_K_M | 3.28GB | |
|
| [multimaster-7b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q3_K_L.gguf) | Q3_K_L | 3.56GB | |
|
| [multimaster-7b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.IQ4_XS.gguf) | IQ4_XS | 3.67GB | |
|
| [multimaster-7b.Q4_0.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q4_0.gguf) | Q4_0 | 3.83GB | |
|
| [multimaster-7b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.IQ4_NL.gguf) | IQ4_NL | 3.87GB | |
|
| [multimaster-7b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q4_K_S.gguf) | Q4_K_S | 3.86GB | |
|
| [multimaster-7b.Q4_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q4_K.gguf) | Q4_K | 4.07GB | |
|
| [multimaster-7b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q4_K_M.gguf) | Q4_K_M | 4.07GB | |
|
| [multimaster-7b.Q4_1.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q4_1.gguf) | Q4_1 | 4.24GB | |
|
| [multimaster-7b.Q5_0.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q5_0.gguf) | Q5_0 | 4.65GB | |
|
| [multimaster-7b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q5_K_S.gguf) | Q5_K_S | 4.65GB | |
|
| [multimaster-7b.Q5_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q5_K.gguf) | Q5_K | 4.78GB | |
|
| [multimaster-7b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q5_K_M.gguf) | Q5_K_M | 4.78GB | |
|
| [multimaster-7b.Q5_1.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q5_1.gguf) | Q5_1 | 5.07GB | |
|
| [multimaster-7b.Q6_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q6_K.gguf) | Q6_K | 5.53GB | |
|
| [multimaster-7b.Q8_0.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-gguf/blob/main/multimaster-7b.Q8_0.gguf) | Q8_0 | 7.17GB | |
|
|
|
|
|
|
|
|
|
Original model description: |
|
--- |
|
license: apache-2.0 |
|
language: |
|
- en |
|
library_name: transformers |
|
tags: |
|
- moe |
|
- moerge |
|
--- |
|
|
|
# Multi Master 7B |
|
|
|
![img](./multimaster.png) |
|
|
|
A quick multi-disciplinary fine tune of openchat/openchat-3.5-0106 using an alpaca-style dataset across different disciplines. I used LORA adapters that I then merged back into the main model for ease of use. |
|
|
|
# Prompting |
|
|
|
## Prompt Template for alpaca style |
|
|
|
``` |
|
### Instruction: |
|
|
|
<prompt> (without the <>) |
|
|
|
### Response: |
|
``` |
|
|
|
## Sample Code |
|
|
|
```python |
|
import torch |
|
from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
|
torch.set_default_device("cuda") |
|
|
|
model = AutoModelForCausalLM.from_pretrained("ibivibiv/multimaster-7b", torch_dtype="auto", device_config='auto') |
|
tokenizer = AutoTokenizer.from_pretrained("ibivibiv/multimaster-7b") |
|
|
|
inputs = tokenizer("### Instruction: Who would when in an arm wrestling match between Abraham Lincoln and Chuck Norris?\nA. Abraham Lincoln \nB. Chuck Norris\n### Response:\n", return_tensors="pt", return_attention_mask=False) |
|
|
|
outputs = model.generate(**inputs, max_length=200) |
|
text = tokenizer.batch_decode(outputs)[0] |
|
print(text) |
|
``` |
|
|
|
# Model Details |
|
* **Trained by**: [ibivibiv](https://huggingface.co/ibivibiv) |
|
* **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers) |
|
* **Model type:** **multimaster-7b** is a lora tuned version of openchat/openchat-3.5-0106 with the adapter merged back into the main model |
|
* **Language(s)**: English |
|
* **Purpose**: This model is a focus on multi-disciplinary model tuning |
|
|
|
# Benchmark Scores |
|
|
|
coming soon |
|
|
|
## Citations |
|
|
|
``` |
|
@misc{open-llm-leaderboard, |
|
author = {Edward Beeching and Clémentine Fourrier and Nathan Habib and Sheon Han and Nathan Lambert and Nazneen Rajani and Omar Sanseviero and Lewis Tunstall and Thomas Wolf}, |
|
title = {Open LLM Leaderboard}, |
|
year = {2023}, |
|
publisher = {Hugging Face}, |
|
howpublished = "\url{https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard}" |
|
} |
|
``` |
|
``` |
|
@software{eval-harness, |
|
author = {Gao, Leo and |
|
Tow, Jonathan and |
|
Biderman, Stella and |
|
Black, Sid and |
|
DiPofi, Anthony and |
|
Foster, Charles and |
|
Golding, Laurence and |
|
Hsu, Jeffrey and |
|
McDonell, Kyle and |
|
Muennighoff, Niklas and |
|
Phang, Jason and |
|
Reynolds, Laria and |
|
Tang, Eric and |
|
Thite, Anish and |
|
Wang, Ben and |
|
Wang, Kevin and |
|
Zou, Andy}, |
|
title = {A framework for few-shot language model evaluation}, |
|
month = sep, |
|
year = 2021, |
|
publisher = {Zenodo}, |
|
version = {v0.0.1}, |
|
doi = {10.5281/zenodo.5371628}, |
|
url = {https://doi.org/10.5281/zenodo.5371628} |
|
} |
|
``` |
|
``` |
|
@misc{clark2018think, |
|
title={Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge}, |
|
author={Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord}, |
|
year={2018}, |
|
eprint={1803.05457}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.AI} |
|
} |
|
``` |
|
``` |
|
@misc{zellers2019hellaswag, |
|
title={HellaSwag: Can a Machine Really Finish Your Sentence?}, |
|
author={Rowan Zellers and Ari Holtzman and Yonatan Bisk and Ali Farhadi and Yejin Choi}, |
|
year={2019}, |
|
eprint={1905.07830}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
} |
|
``` |
|
``` |
|
@misc{hendrycks2021measuring, |
|
title={Measuring Massive Multitask Language Understanding}, |
|
author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt}, |
|
year={2021}, |
|
eprint={2009.03300}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CY} |
|
} |
|
``` |
|
``` |
|
@misc{lin2022truthfulqa, |
|
title={TruthfulQA: Measuring How Models Mimic Human Falsehoods}, |
|
author={Stephanie Lin and Jacob Hilton and Owain Evans}, |
|
year={2022}, |
|
eprint={2109.07958}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
} |
|
``` |
|
``` |
|
@misc{DBLP:journals/corr/abs-1907-10641, |
|
title={{WINOGRANDE:} An Adversarial Winograd Schema Challenge at Scale}, |
|
author={Keisuke Sakaguchi and Ronan Le Bras and Chandra Bhagavatula and Yejin Choi}, |
|
year={2019}, |
|
eprint={1907.10641}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
} |
|
``` |
|
``` |
|
@misc{DBLP:journals/corr/abs-2110-14168, |
|
title={Training Verifiers to Solve Math Word Problems}, |
|
author={Karl Cobbe and |
|
Vineet Kosaraju and |
|
Mohammad Bavarian and |
|
Mark Chen and |
|
Heewoo Jun and |
|
Lukasz Kaiser and |
|
Matthias Plappert and |
|
Jerry Tworek and |
|
Jacob Hilton and |
|
Reiichiro Nakano and |
|
Christopher Hesse and |
|
John Schulman}, |
|
year={2021}, |
|
eprint={2110.14168}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
} |
|
``` |
|
|
|
|