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README.md

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+---
+base_model: VAGOsolutions/SauerkrautLM-13b-v1
+inference: false
+language:
+- de
+- en
+library_name: transformers
+license: llama2
+model_creator: VAGO solutions
+model_name: SauerkrautLM 13B v1
+model_type: llama
+pipeline_tag: text-generation
+prompt_template: "Ein Chat zwischen einem Benutzer und einem KI-Assistenten. Der KI-Assistent\
+  \ gibt hilfreiche, detaillierte und h\xF6fliche Antworten. \nUser: {prompt} \nAssistant:\n"
+quantized_by: TheBloke
+---
+
+<!-- header start -->
+<!-- 200823 -->
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+    <div style="display: flex; flex-direction: column; align-items: flex-start;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/theblokeai">Chat & support: TheBloke's Discord server</a></p>
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+<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 -->
+
+# SauerkrautLM 13B v1 - GGUF
+- Model creator: [VAGO solutions](https://huggingface.co/VAGOsolutions)
+- Original model: [SauerkrautLM 13B v1](https://huggingface.co/VAGOsolutions/SauerkrautLM-13b-v1)
+
+<!-- description start -->
+## Description
+
+This repo contains GGUF format model files for [VAGO solutions's SauerkrautLM 13B v1](https://huggingface.co/VAGOsolutions/SauerkrautLM-13b-v1).
+
+<!-- description end -->
+<!-- README_GGUF.md-about-gguf start -->
+### About GGUF
+
+GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.
+
+Here is an incomplate list of clients and libraries that are known to support GGUF:
+
+* [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option.
+* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
+* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
+* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration.
+* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
+* [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
+* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.
+* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
+* [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
+
+<!-- README_GGUF.md-about-gguf end -->
+<!-- repositories-available start -->
+## Repositories available
+
+* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-AWQ)
+* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GPTQ)
+* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF)
+* [VAGO solutions's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/VAGOsolutions/SauerkrautLM-13b-v1)
+<!-- repositories-available end -->
+
+<!-- prompt-template start -->
+## Prompt template: Sauerkraut
+
+```
+Ein Chat zwischen einem Benutzer und einem KI-Assistenten. Der KI-Assistent gibt hilfreiche, detaillierte und höfliche Antworten. 
+User: {prompt} 
+Assistant:
+
+```
+
+<!-- prompt-template end -->
+
+
+<!-- compatibility_gguf start -->
+## Compatibility
+
+These quantised GGUFv2 files are compatible with llama.cpp from August 27th onwards, as of commit [d0cee0d](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221)
+
+They are also compatible with many third party UIs and libraries - please see the list at the top of this README.
+
+## Explanation of quantisation methods
+<details>
+  <summary>Click to see details</summary>
+
+The new methods available are:
+* GGML_TYPE_Q2_K - "type-1" 2-bit quantization in super-blocks containing 16 blocks, each block having 16 weight. Block scales and mins are quantized with 4 bits. This ends up effectively using 2.5625 bits per weight (bpw)
+* GGML_TYPE_Q3_K - "type-0" 3-bit quantization in super-blocks containing 16 blocks, each block having 16 weights. Scales are quantized with 6 bits. This end up using 3.4375 bpw.
+* GGML_TYPE_Q4_K - "type-1" 4-bit quantization in super-blocks containing 8 blocks, each block having 32 weights. Scales and mins are quantized with 6 bits. This ends up using 4.5 bpw.
+* GGML_TYPE_Q5_K - "type-1" 5-bit quantization. Same super-block structure as GGML_TYPE_Q4_K resulting in 5.5 bpw
+* GGML_TYPE_Q6_K - "type-0" 6-bit quantization. Super-blocks with 16 blocks, each block having 16 weights. Scales are quantized with 8 bits. This ends up using 6.5625 bpw
+
+Refer to the Provided Files table below to see what files use which methods, and how.
+</details>
+<!-- compatibility_gguf end -->
+
+<!-- README_GGUF.md-provided-files start -->
+## Provided files
+
+| Name | Quant method | Bits | Size | Max RAM required | Use case |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+| [sauerkrautlm-13b-v1.Q2_K.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q2_K.gguf) | Q2_K | 2 | 5.43 GB| 7.93 GB | smallest, significant quality loss - not recommended for most purposes |
+| [sauerkrautlm-13b-v1.Q3_K_S.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q3_K_S.gguf) | Q3_K_S | 3 | 5.66 GB| 8.16 GB | very small, high quality loss |
+| [sauerkrautlm-13b-v1.Q3_K_M.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q3_K_M.gguf) | Q3_K_M | 3 | 6.34 GB| 8.84 GB | very small, high quality loss |
+| [sauerkrautlm-13b-v1.Q3_K_L.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q3_K_L.gguf) | Q3_K_L | 3 | 6.93 GB| 9.43 GB | small, substantial quality loss |
+| [sauerkrautlm-13b-v1.Q4_0.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q4_0.gguf) | Q4_0 | 4 | 7.37 GB| 9.87 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [sauerkrautlm-13b-v1.Q4_K_S.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q4_K_S.gguf) | Q4_K_S | 4 | 7.41 GB| 9.91 GB | small, greater quality loss |
+| [sauerkrautlm-13b-v1.Q4_K_M.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q4_K_M.gguf) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
+| [sauerkrautlm-13b-v1.Q5_0.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q5_0.gguf) | Q5_0 | 5 | 8.97 GB| 11.47 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [sauerkrautlm-13b-v1.Q5_K_S.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q5_K_S.gguf) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
+| [sauerkrautlm-13b-v1.Q5_K_M.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q5_K_M.gguf) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
+| [sauerkrautlm-13b-v1.Q6_K.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q6_K.gguf) | Q6_K | 6 | 10.68 GB| 13.18 GB | very large, extremely low quality loss |
+| [sauerkrautlm-13b-v1.Q8_0.gguf](https://huggingface.co/TheBloke/SauerkrautLM-13B-v1-GGUF/blob/main/sauerkrautlm-13b-v1.Q8_0.gguf) | Q8_0 | 8 | 13.83 GB| 16.33 GB | very large, extremely low quality loss - not recommended |
+
+**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.
+
+
+
+<!-- README_GGUF.md-provided-files end -->
+
+<!-- README_GGUF.md-how-to-download start -->
+## How to download GGUF files
+
+**Note for manual downloaders:** You almost never want to clone the entire repo! Multiple different quantisation formats are provided, and most users only want to pick and download a single file.
+
+The following clients/libraries will automatically download models for you, providing a list of available models to choose from:
+- LM Studio
+- LoLLMS Web UI
+- Faraday.dev
+
+### In `text-generation-webui`
+
+Under Download Model, you can enter the model repo: TheBloke/SauerkrautLM-13B-v1-GGUF and below it, a specific filename to download, such as: sauerkrautlm-13b-v1.Q4_K_M.gguf.
+
+Then click Download.
+
+### On the command line, including multiple files at once
+
+I recommend using the `huggingface-hub` Python library:
+
+```shell
+pip3 install huggingface-hub
+```
+
+Then you can download any individual model file to the current directory, at high speed, with a command like this:
+
+```shell
+huggingface-cli download TheBloke/SauerkrautLM-13B-v1-GGUF sauerkrautlm-13b-v1.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
+```
+
+<details>
+  <summary>More advanced huggingface-cli download usage</summary>
+
+You can also download multiple files at once with a pattern:
+
+```shell
+huggingface-cli download TheBloke/SauerkrautLM-13B-v1-GGUF --local-dir . --local-dir-use-symlinks False --include='*Q4_K*gguf'
+```
+
+For more documentation on downloading with `huggingface-cli`, please see: [HF -> Hub Python Library -> Download files -> Download from the CLI](https://huggingface.co/docs/huggingface_hub/guides/download#download-from-the-cli).
+
+To accelerate downloads on fast connections (1Gbit/s or higher), install `hf_transfer`:
+
+```shell
+pip3 install hf_transfer
+```
+
+And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
+
+```shell
+HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/SauerkrautLM-13B-v1-GGUF sauerkrautlm-13b-v1.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
+```
+
+Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command.
+</details>
+<!-- README_GGUF.md-how-to-download end -->
+
+<!-- README_GGUF.md-how-to-run start -->
+## Example `llama.cpp` command
+
+Make sure you are using `llama.cpp` from commit [d0cee0d](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
+
+```shell
+./main -ngl 32 -m sauerkrautlm-13b-v1.Q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Ein Chat zwischen einem Benutzer und einem KI-Assistenten. Der KI-Assistent gibt hilfreiche, detaillierte und höfliche Antworten. \nUser: {prompt} \nAssistant:"
+```
+
+Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
+
+Change `-c 4096` to the desired sequence length. For extended sequence models - eg 8K, 16K, 32K - the necessary RoPE scaling parameters are read from the GGUF file and set by llama.cpp automatically.
+
+If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`
+
+For other parameters and how to use them, please refer to [the llama.cpp documentation](https://github.com/ggerganov/llama.cpp/blob/master/examples/main/README.md)
+
+## How to run in `text-generation-webui`
+
+Further instructions here: [text-generation-webui/docs/llama.cpp.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp.md).
+
+## How to run from Python code
+
+You can use GGUF models from Python using the [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) or [ctransformers](https://github.com/marella/ctransformers) libraries.
+
+### How to load this model in Python code, using ctransformers
+
+#### First install the package
+
+Run one of the following commands, according to your system:
+
+```shell
+# Base ctransformers with no GPU acceleration
+pip install ctransformers
+# Or with CUDA GPU acceleration
+pip install ctransformers[cuda]
+# Or with AMD ROCm GPU acceleration (Linux only)
+CT_HIPBLAS=1 pip install ctransformers --no-binary ctransformers
+# Or with Metal GPU acceleration for macOS systems only
+CT_METAL=1 pip install ctransformers --no-binary ctransformers
+```
+
+#### Simple ctransformers example code
+
+```python
+from ctransformers import AutoModelForCausalLM
+
+# Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
+llm = AutoModelForCausalLM.from_pretrained("TheBloke/SauerkrautLM-13B-v1-GGUF", model_file="sauerkrautlm-13b-v1.Q4_K_M.gguf", model_type="llama", gpu_layers=50)
+
+print(llm("AI is going to"))
+```
+
+## How to use with LangChain
+
+Here are guides on using llama-cpp-python and ctransformers with LangChain:
+
+* [LangChain + llama-cpp-python](https://python.langchain.com/docs/integrations/llms/llamacpp)
+* [LangChain + ctransformers](https://python.langchain.com/docs/integrations/providers/ctransformers)
+
+<!-- README_GGUF.md-how-to-run end -->
+
+<!-- footer start -->
+<!-- 200823 -->
+## Discord
+
+For further support, and discussions on these models and AI in general, join us at:
+
+[TheBloke AI's Discord server](https://discord.gg/theblokeai)
+
+## 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.
+
+Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.
+
+* Patreon: https://patreon.com/TheBlokeAI
+* Ko-Fi: https://ko-fi.com/TheBlokeAI
+
+**Special thanks to**: Aemon Algiz.
+
+**Patreon special mentions**: Pierre Kircher, Stanislav Ovsiannikov, Michael Levine, Eugene Pentland, Andrey, 준교 김, Randy H, Fred von Graf, Artur Olbinski, Caitlyn Gatomon, terasurfer, Jeff Scroggin, James Bentley, Vadim, Gabriel Puliatti, Harry Royden McLaughlin, Sean Connelly, Dan Guido, Edmond Seymore, Alicia Loh, subjectnull, AzureBlack, Manuel Alberto Morcote, Thomas Belote, Lone Striker, Chris Smitley, Vitor Caleffi, Johann-Peter Hartmann, Clay Pascal, biorpg, Brandon Frisco, sidney chen, transmissions 11, Pedro Madruga, jinyuan sun, Ajan Kanaga, Emad Mostaque, Trenton Dambrowitz, Jonathan Leane, Iucharbius, usrbinkat, vamX, George Stoitzev, Luke Pendergrass, theTransient, Olakabola, Swaroop Kallakuri, Cap'n Zoog, Brandon Phillips, Michael Dempsey, Nikolai Manek, danny, Matthew Berman, Gabriel Tamborski, alfie_i, Raymond Fosdick, Tom X Nguyen, Raven Klaugh, LangChain4j, Magnesian, Illia Dulskyi, David Ziegler, Mano Prime, Luis Javier Navarrete Lozano, Erik Bjäreholt, 阿明, Nathan Dryer, Alex, Rainer Wilmers, zynix, TL, Joseph William Delisle, John Villwock, Nathan LeClaire, Willem Michiel, Joguhyik, GodLy, OG, Alps Aficionado, Jeffrey Morgan, ReadyPlayerEmma, Tiffany J. Kim, Sebastain Graf, Spencer Kim, Michael Davis, webtim, Talal Aujan, knownsqashed, John Detwiler, Imad Khwaja, Deo Leter, Jerry Meng, Elijah Stavena, Rooh Singh, Pieter, SuperWojo, Alexandros Triantafyllidis, Stephen Murray, Ai Maven, ya boyyy, Enrico Ros, Ken Nordquist, Deep Realms, Nicholas, Spiking Neurons AB, Elle, Will Dee, Jack West, RoA, Luke @flexchar, Viktor Bowallius, Derek Yates, Subspace Studios, jjj, Toran Billups, Asp the Wyvern, Fen Risland, Ilya, NimbleBox.ai, Chadd, Nitin Borwankar, Emre, Mandus, Leonard Tan, Kalila, K, Trailburnt, S_X, Cory Kujawski
+
+
+Thank you to all my generous patrons and donaters!
+
+And thank you again to a16z for their generous grant.
+
+<!-- footer end -->
+
+<!-- original-model-card start -->
+# Original model card: VAGO solutions's SauerkrautLM 13B v1
+
+
+![SauerkrautLM](images/SauerkrautLM.png "SauerkrautLM")
+## VAGO solutions SauerkrautLM
+Introducing SauerkrautLM-v1 - Your German Language Powerhouse!
+
+We are thrilled to unveil our **very first release**, **SauerkrautLM-v1**. This remarkable creation marks a significant milestone as it is specifically **tailored for the German-speaking community**. In a landscape where German language models are scarce, we are proud to offer a solution that fills this void.
+What sets SauerkrautLM-v1 apart is its versatility. Whether you are an individual looking to harness its capabilities for personal use or a business seeking to integrate it into your projects, our model is designed to accommodate all. It operates under the LLAMA 2 License, providing you with the freedom to explore its potential in both private and commercial applications.
+Performance is at the heart of SauerkrautLM-v1. We put it to the **test using a customized version of MT-Bench for the German language**, and the results speak volumes. It currently stands as the most robust German Language Model on Hugging Face (based on german mt-bench results), showcasing its exceptional capabilities. Rest assured, this model is here to shine and set new standards. And the best thing is it comes in three different sizes (3B, 7B, 13B) to address your individual needs.
+Our model's journey began with meticulous training using an **augmented dataset within the QLoRA approach**. This is just the beginning of our model series, promising even more innovative and powerful solutions in the future.
+
+Join us on this exciting adventure as we redefine the possibilities of language modeling for the German-speaking world.
+SauerkrautLM-v1 is here to empower your language-related endeavors like never before.
+
+## All Models
+
+| Model | HF    | GPTQ  | GGUF  |
+|-------|-------|-------|-------|
+| SauerkrautLM-3b-v1   | [Link](https://huggingface.co/VAGOsolutions/SauerkrautLM-3b-v1) | soon | soon |
+| SauerkrautLM-7b-v1   | [Link](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-v1) | soon | soon |
+| SauerkrautLM-7b-v1-mistral   | [Link](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-v1-mistral) | soon | soon |
+| SauerkrautLM-13b-v1   | [Link](https://huggingface.co/VAGOsolutions/SauerkrautLM-13b-v1) | soon | soon |
+
+## Model Details
+**SauerkrautLM-13b-v1**
+
+**Training Dataset:**
+
+SauerkrautLM was trained with mix of German data augmentation and translated data.
+We found, that only a simple translation of training data can lead to unnatural German phrasings.
+Data augmentation techniques were used to grant grammatical, syntactical correctness and a more natural German wording in our training data.
+
+**Training Procedure:**
+
+SauerkrautLM-13b-v1 was fine-tuned using QLoRA on 1 A100 80GB with Axolotl.
+
+- **Trained by:** SauerkrautLM-v1 trained by VAGO solutions
+- **Model Type:** SauerkrautLM-v1 is an auto-regressive language model based on the transformer architecture
+- **Language(s):** German, English
+- **License:** [LLAMA 2 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/meta-llama/Llama-2-70b/raw/main/LICENSE.txt)
+- **Contact:** [Website](https://vago-solutions.de/#Kontakt) [David Golchinfar](mailto:[email protected])
+
+**Prompt Template:**
+
+```
+Ein Chat zwischen einem Benutzer und einem KI-Assistenten. Der KI-Assistent gibt hilfreiche, detaillierte und höfliche Antworten.
+User: {prompt}
+Assistant:
+```
+
+## Evaluation
+**[MT-Bench-TrueGerman](https://huggingface.co/datasets/VAGOsolutions/MT-Bench-TrueGerman)**
+
+ ![First Turn](images/FirstTurn.PNG "First Turn")
+ ![Second Turn](images/SecondTurn.PNG "Second Turn")
+ ![Average](images/Average.PNG "Average")
+
+ ![Category Scores](images/SauerkrautLM-13b.png "Category Scores")
+ ![Category Plot](images/SauerkrautLM-13b-v1.png "Category Plot")
+
+## Disclaimer
+Our models have been meticulously trained on extensive datasets. While we have made diligent efforts to thoroughly screen and eliminate any instances of coarse or inappropriate language from our data, we must inform users that despite our best efforts in data cleansing, the possibility of some such content slipping through cannot be entirely ruled out.
+Furthermore, it is important to note that we have implemented filters within our models; however, we cannot always guarantee consistently appropriate behavior. Therefore, if you encounter any issues or come across inappropriate content, we kindly request that you inform us through the contact information provided.
+Additionally, it is essential to understand that the licensing of these models does not constitute legal advice. We are not held responsible for the actions of third parties who utilize our models. These models may be employed for commercial purposes, and the original Llama2 license remains applicable and is included with the model files.
+
+## Contact
+If you are interested in customized LLMs for business applications, please get in contact with us via our website or contact us at [Dr. Daryoush Vaziri](mailto:[email protected]). We are also grateful for your feedback and suggestions.
+
+## Collaborations
+We are also keenly seeking support and investment for our startup, VAGO solutions, where we continuously advance the development of robust language models designed to address a diverse range of purposes and requirements. If the prospect of collaboratively navigating future challenges excites you, we warmly invite you to reach out to us.
+
+<!-- original-model-card end -->