Upload README.md

README.md

@@ -1,10 +1,11 @@
 ---
 datasets:
-- garage-bAInd/OpenPlatypus
+- garage-bAInd/Open-Platypus
+- Open-Orca/OpenOrca
 inference: false
 language:
 - en
-license: other
+license: llama2
 model_creator: garage-bAInd
 model_link: https://huggingface.co/garage-bAInd/Platypus2-70B-instruct
 model_name: Platypus2 70B Instruct
@@ -13,17 +14,20 @@ quantized_by: TheBloke
 ---
 
 <!-- header start -->
-<div style="width: 100%;">
-    <img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+<!-- 200823 -->
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
 </div>
 <div style="display: flex; justify-content: space-between; width: 100%;">
     <div style="display: flex; flex-direction: column; align-items: flex-start;">
-        <p><a href="https://discord.gg/theblokeai">Chat & support: my new Discord server</a></p>
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/theblokeai">Chat & support: TheBloke's Discord server</a></p>
     </div>
     <div style="display: flex; flex-direction: column; align-items: flex-end;">
-        <p><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
     </div>
 </div>
+<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">TheBloke's LLM work is generously supported by a grant from <a href="https://a16z.com">andreessen horowitz (a16z)</a></p></div>
+<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
 <!-- header end -->
 
 # Platypus2 70B Instruct - GGML
@@ -34,6 +38,14 @@ quantized_by: TheBloke
 
 This repo contains GGML format model files for [garage-bAInd's Platypus2 70B Instruct](https://huggingface.co/garage-bAInd/Platypus2-70B-instruct).
 
+### Important note regarding GGML files.
+
+The GGML format has now been superseded by GGUF. As of August 21st 2023, [llama.cpp](https://github.com/ggerganov/llama.cpp) no longer supports GGML models. Third party clients and libraries are expected to still support it for a time, but many may also drop support.
+
+Please use the GGUF models instead.
+
+### About GGML
+
 GPU acceleration is now available for Llama 2 70B GGML files, with both CUDA (NVidia) and Metal (macOS). The following clients/libraries are known to work with these files, including with GPU acceleration:
 * [llama.cpp](https://github.com/ggerganov/llama.cpp), commit `e76d630` and later.
 * [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI.
@@ -45,7 +57,8 @@ GPU acceleration is now available for Llama 2 70B GGML files, with both CUDA (NV
 ## Repositories available
 
 * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GPTQ)
-* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML)
+* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGUF)
+* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference (deprecated)](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML)
 * [garage-bAInd's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/garage-bAInd/Platypus2-70B-instruct)
 
 ## Prompt template: Alpaca
@@ -57,12 +70,17 @@ Below is an instruction that describes a task. Write a response that appropriate
 {prompt}
 
 ### Response:
+
 ```
 
 <!-- compatibility_ggml start -->
 ## Compatibility
 
-### Requires llama.cpp [commit `e76d630`](https://github.com/ggerganov/llama.cpp/commit/e76d630df17e235e6b9ef416c45996765d2e36fb) or later.
+### Works with llama.cpp [commit `e76d630`](https://github.com/ggerganov/llama.cpp/commit/e76d630df17e235e6b9ef416c45996765d2e36fb) until August 21st, 2023
+
+Will not work with `llama.cpp` after commit [dadbed99e65252d79f81101a392d0d6497b86caa](https://github.com/ggerganov/llama.cpp/commit/dadbed99e65252d79f81101a392d0d6497b86caa).
+
+For compatibility with latest llama.cpp, please use GGUF files instead.
 
 Or one of the other tools and libraries listed above.
 
@@ -91,57 +109,29 @@ Refer to the Provided Files table below to see what files use which methods, and
 | Name | Quant method | Bits | Size | Max RAM required | Use case |
 | ---- | ---- | ---- | ---- | ---- | ----- |
 | [platypus2-70b-instruct.ggmlv3.q2_K.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q2_K.bin) | q2_K | 2 | 28.59 GB| 31.09 GB | New k-quant method. Uses GGML_TYPE_Q4_K for the attention.vw and feed_forward.w2 tensors, GGML_TYPE_Q2_K for the other tensors. |
-| [platypus2-70b-instruct.ggmlv3.q3_K_L.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q3_K_L.bin) | q3_K_L | 3 | 36.15 GB| 38.65 GB | New k-quant method. Uses GGML_TYPE_Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
-| [platypus2-70b-instruct.ggmlv3.q3_K_M.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q3_K_M.bin) | q3_K_M | 3 | 33.04 GB| 35.54 GB | New k-quant method. Uses GGML_TYPE_Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
 | [platypus2-70b-instruct.ggmlv3.q3_K_S.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q3_K_S.bin) | q3_K_S | 3 | 29.75 GB| 32.25 GB | New k-quant method. Uses GGML_TYPE_Q3_K for all tensors |
+| [platypus2-70b-instruct.ggmlv3.q3_K_M.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q3_K_M.bin) | q3_K_M | 3 | 33.04 GB| 35.54 GB | New k-quant method. Uses GGML_TYPE_Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
+| [platypus2-70b-instruct.ggmlv3.q3_K_L.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q3_K_L.bin) | q3_K_L | 3 | 36.15 GB| 38.65 GB | New k-quant method. Uses GGML_TYPE_Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
 | [platypus2-70b-instruct.ggmlv3.q4_0.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q4_0.bin) | q4_0 | 4 | 38.87 GB| 41.37 GB | Original quant method, 4-bit. |
-| [platypus2-70b-instruct.ggmlv3.q4_1.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q4_1.bin) | q4_1 | 4 | 43.17 GB| 45.67 GB | Original quant method, 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
-| [platypus2-70b-instruct.ggmlv3.q4_K_M.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q4_K_M.bin) | q4_K_M | 4 | 41.38 GB| 43.88 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q4_K |
 | [platypus2-70b-instruct.ggmlv3.q4_K_S.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q4_K_S.bin) | q4_K_S | 4 | 38.87 GB| 41.37 GB | New k-quant method. Uses GGML_TYPE_Q4_K for all tensors |
+| [platypus2-70b-instruct.ggmlv3.q4_K_M.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q4_K_M.bin) | q4_K_M | 4 | 41.38 GB| 43.88 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q4_K |
+| [platypus2-70b-instruct.ggmlv3.q4_1.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q4_1.bin) | q4_1 | 4 | 43.17 GB| 45.67 GB | Original quant method, 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
 | [platypus2-70b-instruct.ggmlv3.q5_0.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q5_0.bin) | q5_0 | 5 | 47.46 GB| 49.96 GB | Original quant method, 5-bit. Higher accuracy, higher resource usage and slower inference. |
-| [platypus2-70b-instruct.ggmlv3.q5_K_M.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q5_K_M.bin) | q5_K_M | 5 | 48.75 GB| 51.25 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q5_K |
 | [platypus2-70b-instruct.ggmlv3.q5_K_S.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q5_K_S.bin) | q5_K_S | 5 | 47.46 GB| 49.96 GB | New k-quant method. Uses GGML_TYPE_Q5_K for all tensors |
-| platypus2-70b-instruct.ggmlv3.q5_1.bin | q5_1 | 5 | 51.76 GB | 54.26 GB | Original quant method, 5-bit. Higher accuracy, slower inference than q5_0. |
-| platypus2-70b-instruct.ggmlv3.q6_K.bin | q6_K | 6 | 56.59 GB | 59.09 GB | New k-quant method. Uses GGML_TYPE_Q8_K - 6-bit quantization - for all tensors |
-| platypus2-70b-instruct.ggmlv3.q8_0.bin | q8_0 | 8 | 73.23 GB | 75.73 GB | Original llama.cpp quant method, 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
+| [platypus2-70b-instruct.ggmlv3.q5_K_M.bin](https://huggingface.co/TheBloke/Platypus2-70B-Instruct-GGML/blob/main/platypus2-70b-instruct.ggmlv3.q5_K_M.bin) | q5_K_M | 5 | 48.75 GB| 51.25 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q5_K |
 
 **Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
 
-### q5_1, q6_K and q8_0 files require expansion from archive
-
-**Note:** HF does not support uploading files larger than 50GB. Therefore I have uploaded the q6_K and q8_0 files as multi-part ZIP files. They are not compressed, they are just for storing a .bin file in two parts.
+## How to run in `llama.cpp`
 
-<details>
-  <summary>Click for instructions regarding q5_1, q6_K and q8_0 files</summary>
-  
-### q5_1
-Please download:
-* `platypus2-70b-instruct.ggmlv3.q5_1.zip`
-* `platypus2-70b-instruct.ggmlv3.q5_1.z01`
- 
-### q6_K 
-Please download:
-* `platypus2-70b-instruct.ggmlv3.q6_K.zip`
-* `platypus2-70b-instruct.ggmlv3.q6_K.z01`
-
-### q8_0
-Please download:
-* `platypus2-70b-instruct.ggmlv3.q8_0.zip`
-* `platypus2-70b-instruct.ggmlv3.q8_0.z01`
-
-Then extract the .zip archive. This will will expand both parts automatically. On Linux I found I had to use `7zip` - the basic `unzip` tool did not work. Example:
-```
-sudo apt update -y && sudo apt install 7zip
-7zz x platypus2-70b-instruct.ggmlv3.q6_K.zip
-```
-</details>
+Make sure you are using `llama.cpp` from commit [dadbed99e65252d79f81101a392d0d6497b86caa](https://github.com/ggerganov/llama.cpp/commit/dadbed99e65252d79f81101a392d0d6497b86caa) or earlier.
 
-## How to run in `llama.cpp`
+For compatibility with latest llama.cpp, please use GGUF files instead.
 
 I use the following command line; adjust for your tastes and needs:
 
 ```
-./main -t 10 -ngl 40 -gqa 8 -m platypus2-70b-instruct.ggmlv3.q4_K_M.bin --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\nWrite a story about llamas\n\n### Response:"
+./main -t 10 -ngl 40 -gqa 8 -m platypus2-70b-instruct.ggmlv3.q4_K_M.bin --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n{prompt}\n\n### Response:"
 ```
 Change `-t 10` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`. If you are fully offloading the model to GPU, use `-t 1`
 
@@ -160,6 +150,7 @@ For other parameters and how to use them, please refer to [the llama.cpp documen
 Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).
 
 <!-- footer start -->
+<!-- 200823 -->
 ## Discord
 
 For further support, and discussions on these models and AI in general, join us at:
@@ -179,13 +170,15 @@ Donaters will get priority support on any and all AI/LLM/model questions and req
 * Patreon: https://patreon.com/TheBlokeAI
 * Ko-Fi: https://ko-fi.com/TheBlokeAI
 
-**Special thanks to**: Luke from CarbonQuill, Aemon Algiz.
+**Special thanks to**: Aemon Algiz.
 
-**Patreon special mentions**: Willem Michiel, Ajan Kanaga, Cory Kujawski, Alps Aficionado, Nikolai Manek, Jonathan Leane, Stanislav Ovsiannikov, Michael Levine, Luke Pendergrass, Sid, K, Gabriel Tamborski, Clay Pascal, Kalila, William Sang, Will Dee, Pieter, Nathan LeClaire, ya boyyy, David Flickinger, vamX, Derek Yates, Fen Risland, Jeffrey Morgan, webtim, Daniel P. Andersen, Chadd, Edmond Seymore, Pyrater, Olusegun Samson, Lone Striker, biorpg, alfie_i, Mano Prime, Chris Smitley, Dave, zynix, Trenton Dambrowitz, Johann-Peter Hartmann, Magnesian, Spencer Kim, John Detwiler, Iucharbius, Gabriel Puliatti, LangChain4j, Luke @flexchar, Vadim, Rishabh Srivastava, Preetika Verma, Ai Maven, Femi Adebogun, WelcomeToTheClub, Leonard Tan, Imad Khwaja, Steven Wood, Stefan Sabev, Sebastain Graf, usrbinkat, Dan Guido, Sam, Eugene Pentland, Mandus, transmissions 11, Slarti, Karl Bernard, Spiking Neurons AB, Artur Olbinski, Joseph William Delisle, ReadyPlayerEmma, Olakabola, Asp the Wyvern, Space Cruiser, Matthew Berman, Randy H, subjectnull, danny, John Villwock, Illia Dulskyi, Rainer Wilmers, theTransient, Pierre Kircher, Alexandros Triantafyllidis, Viktor Bowallius, terasurfer, Deep Realms, SuperWojo, senxiiz, Oscar Rangel, Alex, Stephen Murray, Talal Aujan, Raven Klaugh, Sean Connelly, Raymond Fosdick, Fred von Graf, chris gileta, Junyu Yang, Elle
+**Patreon special mentions**: Russ Johnson, J, alfie_i, Alex, NimbleBox.ai, Chadd, Mandus, Nikolai Manek, Ken Nordquist, ya boyyy, Illia Dulskyi, Viktor Bowallius, vamX, Iucharbius, zynix, Magnesian, Clay Pascal, Pierre Kircher, Enrico Ros, Tony Hughes, Elle, Andrey, knownsqashed, Deep Realms, Jerry Meng, Lone Striker, Derek Yates, Pyrater, Mesiah Bishop, James Bentley, Femi Adebogun, Brandon Frisco, SuperWojo, Alps Aficionado, Michael Dempsey, Vitor Caleffi, Will Dee, Edmond Seymore, usrbinkat, LangChain4j, Kacper Wikieł, Luke Pendergrass, John Detwiler, theTransient, Nathan LeClaire, Tiffany J. Kim, biorpg, Eugene Pentland, Stanislav Ovsiannikov, Fred von Graf, terasurfer, Kalila, Dan Guido, Nitin Borwankar, 阿明, Ai Maven, John Villwock, Gabriel Puliatti, Stephen Murray, Asp the Wyvern, danny, Chris Smitley, ReadyPlayerEmma, S_X, Daniel P. Andersen, Olakabola, Jeffrey Morgan, Imad Khwaja, Caitlyn Gatomon, webtim, Alicia Loh, Trenton Dambrowitz, Swaroop Kallakuri, Erik Bjäreholt, Leonard Tan, Spiking Neurons AB, Luke @flexchar, Ajan Kanaga, Thomas Belote, Deo Leter, RoA, Willem Michiel, transmissions 11, subjectnull, Matthew Berman, Joseph William Delisle, David Ziegler, Michael Davis, Johann-Peter Hartmann, Talal Aujan, senxiiz, Artur Olbinski, Rainer Wilmers, Spencer Kim, Fen Risland, Cap'n Zoog, Rishabh Srivastava, Michael Levine, Geoffrey Montalvo, Sean Connelly, Alexandros Triantafyllidis, Pieter, Gabriel Tamborski, Sam, Subspace Studios, Junyu Yang, Pedro Madruga, Vadim, Cory Kujawski, K, Raven Klaugh, Randy H, Mano Prime, Sebastain Graf, Space Cruiser
 
 
 Thank you to all my generous patrons and donaters!
 
+And thank you again to a16z for their generous grant.
+
 <!-- footer end -->
 
 # Original model card: garage-bAInd's Platypus2 70B Instruct
@@ -227,7 +220,9 @@ We use state-of-the-art [Language Model Evaluation Harness](https://github.com/E
 
 ### Training Dataset
 
-STEM and logic based dataset [`garage-bAInd/OpenPlatypus`](https://huggingface.co/datasets/garage-bAInd/OpenPlatypus) [COMING SOON!].
+`garage-bAInd/Platypus2-70B` trained using STEM and logic based dataset [`garage-bAInd/Open-Platypus`](https://huggingface.co/datasets/garage-bAInd/Open-Platypus).
+
+Please see our [paper](https://arxiv.org/abs/2308.07317) and [project webpage](https://platypus-llm.github.io) for additional information.
 
 ### Training Procedure
 
@@ -274,19 +269,29 @@ Llama 2 and fine-tuned variants are a new technology that carries risks with use
 Please see the Responsible Use Guide available at https://ai.meta.com/llama/responsible-use-guide/
 
 ### Citations
-
+```bibtex
+@article{platypus2023,
+    title={Platypus: Quick, Cheap, and Powerful Refinement of LLMs}, 
+    author={Ariel N. Lee and Cole J. Hunter and Nataniel Ruiz},
+    booktitle={arXiv preprint arxiv:2308.07317},
+    year={2023}
+}
+```
 ```bibtex
 @misc{touvron2023llama,
     title={Llama 2: Open Foundation and Fine-Tuned Chat Models}, 
-    author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov and Soumya Batra and Prajjwal Bhargava and Shruti Bhosale and Dan Bikel and Lukas Blecher and Cristian Canton Ferrer and Moya Chen and Guillem Cucurull and David Esiobu and Jude Fernandes and Jeremy Fu and Wenyin Fu and Brian Fuller and Cynthia Gao and Vedanuj Goswami and Naman Goyal and Anthony Hartshorn and Saghar Hosseini and Rui Hou and Hakan Inan and Marcin Kardas and Viktor Kerkez and Madian Khabsa and Isabel Kloumann and Artem Korenev and Punit Singh Koura and Marie-Anne Lachaux and Thibaut Lavril and Jenya Lee and Diana Liskovich and Yinghai Lu and Yuning Mao and Xavier Martinet and Todor Mihaylov and Pushkar Mishra and Igor Molybog and Yixin Nie and Andrew Poulton and Jeremy Reizenstein and Rashi Rungta and Kalyan Saladi and Alan Schelten and Ruan Silva and Eric Michael Smith and Ranjan Subramanian and Xiaoqing Ellen Tan and Binh Tang and Ross Taylor and Adina Williams and Jian Xiang Kuan and Puxin Xu and Zheng Yan and Iliyan Zarov and Yuchen Zhang and Angela Fan and Melanie Kambadur and Sharan Narang and Aurelien Rodriguez and Robert Stojnic and Sergey Edunov and Thomas Scialom},
-    year={2023}
+    author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov       year={2023},
+    eprint={2307.09288},
+    archivePrefix={arXiv},
 }
 ```
 ```bibtex
-@article{hu2021lora,
-  title={LoRA: Low-Rank Adaptation of Large Language Models},
-  author={Hu, Edward J. and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Chen, Weizhu},
-  journal={CoRR},
-  year={2021}
+@inproceedings{
+    hu2022lora,
+    title={Lo{RA}: Low-Rank Adaptation of Large Language Models},
+    author={Edward J Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen-Zhu and Yuanzhi Li and Shean Wang and Lu Wang and Weizhu Chen},
+    booktitle={International Conference on Learning Representations},
+    year={2022},
+    url={https://openreview.net/forum?id=nZeVKeeFYf9}
 }
 ```