Upload README.md

README.md

@@ -1,12 +1,13 @@
 ---
+base_model: https://huggingface.co/bhenrym14/airoboros-l2-13b-2.1-YaRN-64k
 datasets:
 - jondurbin/airoboros-2.1
 inference: false
 license: llama2
 model_creator: bhenrym14
-model_link: https://huggingface.co/bhenrym14/airoboros-l2-13b-2.1-YaRN-64k
 model_name: Airoboros L2 13B 2.1 YaRN 64K
 model_type: llama
+prompt_template: "A chat.\nUSER: {prompt}\nASSISTANT: \n"
 quantized_by: TheBloke
 ---
 
@@ -42,8 +43,9 @@ Multiple GPTQ parameter permutations are provided; see Provided Files below for
 <!-- repositories-available start -->
 ## Repositories available
 
-* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ)
-* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GGUF)
+* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-AWQ)
+* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ)
+* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GGUF)
 * [bhenrym14's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/bhenrym14/airoboros-l2-13b-2.1-YaRN-64k)
 <!-- repositories-available end -->
 
@@ -59,6 +61,7 @@ ASSISTANT:
 
 <!-- prompt-template end -->
 
+
 <!-- README_GPTQ.md-provided-files start -->
 ## Provided files and GPTQ parameters
 
@@ -83,20 +86,20 @@ All recent GPTQ files are made with AutoGPTQ, and all files in non-main branches
 
 | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc |
 | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
-| [main](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ/tree/main) | 4 | 128 | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 7.26 GB | Yes | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. | 
-| [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 8.00 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. | 
-| [gptq-8bit--1g-actorder_True](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ/tree/gptq-8bit--1g-actorder_True) | 8 | None | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 13.36 GB | No | 8-bit, with Act Order. No group size, to lower VRAM requirements and to improve AutoGPTQ speed. | 
-| [gptq-8bit-128g-actorder_True](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ/tree/gptq-8bit-128g-actorder_True) | 8 | 128 | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 13.65 GB | No | 8-bit, with group size 128g for higher inference quality and with Act Order for even higher accuracy. Poor AutoGPTQ CUDA speed. |
+| [main](https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ/tree/main) | 4 | 128 | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 7.26 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. | 
+| [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 8.00 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. | 
+| [gptq-8bit--1g-actorder_True](https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ/tree/gptq-8bit--1g-actorder_True) | 8 | None | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 13.36 GB | No | 8-bit, with Act Order. No group size, to lower VRAM requirements. | 
+| [gptq-8bit-128g-actorder_True](https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ/tree/gptq-8bit-128g-actorder_True) | 8 | 128 | Yes | 0.1 | [c4](https://huggingface.co/datasets/allenai/c4) | 32768 | 13.65 GB | No | 8-bit, with group size 128g for higher inference quality and with Act Order for even higher accuracy. |
 
 <!-- README_GPTQ.md-provided-files end -->
 
 <!-- README_GPTQ.md-download-from-branches start -->
 ## How to download from branches
 
-- In text-generation-webui, you can add `:branch` to the end of the download name, eg `TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ:gptq-4bit-32g-actorder_True`
+- In text-generation-webui, you can add `:branch` to the end of the download name, eg `TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ:main`
 - With Git, you can clone a branch with:
 ```
-git clone --single-branch --branch gptq-4bit-32g-actorder_True https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ
+git clone --single-branch --branch main https://huggingface.co/TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ
 ```
 - In Python Transformers code, the branch is the `revision` parameter; see below.
 <!-- README_GPTQ.md-download-from-branches end -->
@@ -108,13 +111,13 @@ Please make sure you're using the latest version of [text-generation-webui](http
 It is strongly recommended to use the text-generation-webui one-click-installers unless you're sure you know how to make a manual install.
 
 1. Click the **Model tab**.
-2. Under **Download custom model or LoRA**, enter `TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ`.
-  - To download from a specific branch, enter for example `TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ:gptq-4bit-32g-actorder_True`
+2. Under **Download custom model or LoRA**, enter `TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ`.
+  - To download from a specific branch, enter for example `TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ:main`
   - see Provided Files above for the list of branches for each option.
 3. Click **Download**.
 4. The model will start downloading. Once it's finished it will say "Done".
 5. In the top left, click the refresh icon next to **Model**.
-6. In the **Model** dropdown, choose the model you just downloaded: `Airoboros-L2-13B-2.1-YaRN-64K-GPTQ`
+6. In the **Model** dropdown, choose the model you just downloaded: `Airoboros-L2-13B-2_1-YaRN-64K-GPTQ`
 7. The model will automatically load, and is now ready for use!
 8. If you want any custom settings, set them and then click **Save settings for this model** followed by **Reload the Model** in the top right.
   * Note that you do not need to and should not set manual GPTQ parameters any more. These are set automatically from the file `quantize_config.json`.
@@ -155,9 +158,9 @@ pip3 install git+https://github.com/huggingface/transformers.git
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
-model_name_or_path = "TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ"
+model_name_or_path = "TheBloke/Airoboros-L2-13B-2_1-YaRN-64K-GPTQ"
 # To use a different branch, change revision
-# For example: revision="gptq-4bit-32g-actorder_True"
+# For example: revision="main"
 model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
                                              device_map="auto",
                                              trust_remote_code=True,
@@ -215,10 +218,12 @@ For further support, and discussions on these models and AI in general, join us
 
 [TheBloke AI's Discord server](https://discord.gg/theblokeai)
 
-## Thanks, and how to contribute.
+## Thanks, and how to contribute
 
 Thanks to the [chirper.ai](https://chirper.ai) team!
 
+Thanks to Clay from [gpus.llm-utils.org](llm-utils)!
+
 I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
 
 If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
@@ -230,7 +235,7 @@ Donaters will get priority support on any and all AI/LLM/model questions and req
 
 **Special thanks to**: Aemon Algiz.
 
-**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
+**Patreon special mentions**: Alicia Loh, Stephen Murray, K, Ajan Kanaga, RoA, Magnesian, Deo Leter, Olakabola, Eugene Pentland, zynix, Deep Realms, Raymond Fosdick, Elijah Stavena, Iucharbius, Erik Bjäreholt, Luis Javier Navarrete Lozano, Nicholas, theTransient, John Detwiler, alfie_i, knownsqashed, Mano Prime, Willem Michiel, Enrico Ros, LangChain4j, OG, Michael Dempsey, Pierre Kircher, Pedro Madruga, James Bentley, Thomas Belote, Luke @flexchar, Leonard Tan, Johann-Peter Hartmann, Illia Dulskyi, Fen Risland, Chadd, S_X, Jeff Scroggin, Ken Nordquist, Sean Connelly, Artur Olbinski, Swaroop Kallakuri, Jack West, Ai Maven, David Ziegler, Russ Johnson, transmissions 11, John Villwock, Alps Aficionado, Clay Pascal, Viktor Bowallius, Subspace Studios, Rainer Wilmers, Trenton Dambrowitz, vamX, Michael Levine, 준교 김, Brandon Frisco, Kalila, Trailburnt, Randy H, Talal Aujan, Nathan Dryer, Vadim, 阿明, ReadyPlayerEmma, Tiffany J. Kim, George Stoitzev, Spencer Kim, Jerry Meng, Gabriel Tamborski, Cory Kujawski, Jeffrey Morgan, Spiking Neurons AB, Edmond Seymore, Alexandros Triantafyllidis, Lone Striker, Cap'n Zoog, Nikolai Manek, danny, ya boyyy, Derek Yates, usrbinkat, Mandus, TL, Nathan LeClaire, subjectnull, Imad Khwaja, webtim, Raven Klaugh, Asp the Wyvern, Gabriel Puliatti, Caitlyn Gatomon, Joseph William Delisle, Jonathan Leane, Luke Pendergrass, SuperWojo, Sebastain Graf, Will Dee, Fred von Graf, Andrey, Dan Guido, Daniel P. Andersen, Nitin Borwankar, Elle, Vitor Caleffi, biorpg, jjj, NimbleBox.ai, Pieter, Matthew Berman, terasurfer, Michael Davis, Alex, Stanislav Ovsiannikov
 
 
 Thank you to all my generous patrons and donaters!
@@ -244,6 +249,8 @@ And thank you again to a16z for their generous grant.
 
 # Extended Context (via YaRN) Finetune of Llama-2-13b with airoboros-2.1 (fp16)
 
+[TheBloke](https://huggingface.co/TheBloke) has kindly quantized this model to [GGUF](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GGUF) and [GPTQ](https://huggingface.co/TheBloke/Airoboros-L2-13B-2.1-YaRN-64K-GPTQ).
+
 
 ## Overview