Create README.md

README.md

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+---
+base_model: bineric/NorskGPT-Llama3-8b
+tags:
+  - llama
+  - NorskGPT
+  - instruct
+  - finetune
+language:
+  - no
+
+license: cc-by-nc-sa-4.0
+---
+# NorskGPT-Llama-3-8b-v0.1
+
+This model is a Norwegian variant of 
+Meta-Llama-3-8B, fine-tuned on a carefully selected mix of Norwegian instruction pairs. The model is tuned to understand and generate text in Norwegain. 
+
+
+## Intended Use
+
+This model is free to use for personal and research use. However a commercial license is required for commerical applications. 
+This model can be used as an assistant-like chat. Try it out :)
+
+
+## Prompt Template
+
+```
+<|im_start|>system
+Du er NorskGPT ....<|im_end|>
+<|im_start|>user
+Hei<|im_end|>
+<|im_start|>assistant
+Hei, hva kan jeg hjelpe deg med?<|im_end|>
+```
+<!-- description start -->
+## Description
+
+This repo contains GGUF format model files for [NorskGPT-Llama3-8b](https://huggingface.co/bineric/NorskGPT-Llama3-8b).
+
+## License
+[Attribution-NonCommercial-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-nc-sa/4.0/)
+
+
+ This model is free to use for personal and research use. However a commercial license is required for commerical applications.
+ 
+ You are free to:
+
+    Share — copy and redistribute the material in any medium or format
+    Adapt — remix, transform, and build upon the material
+    The licensor cannot revoke these freedoms as long as you follow the license terms.
+
+Under the following terms:
+
+    Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
+    NonCommercial — You may not use the material for commercial purposes .
+    ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
+    No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
+
+
+<!-- description end -->
+<!-- README_GGUF.md-about-gguf start -->
+### About GGUF
+
+Here is an incomplete 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.
+* [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
+* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
+* [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.
+* [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.
+* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models.
+
+<!-- README_GGUF.md-about-gguf end -->
+
+## Prompt template: ChatML
+
+```
+<|im_start|>system
+{system_message}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+
+```
+
+<!-- prompt-template end -->
+
+
+
+
+## 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 |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+| NorskGPT-Llama3-8b.Q2_K.gguf | Q2_K | 2 | 2.72 GB| 5.22 GB | significant quality loss - not recommended for most purposes |
+| NorskGPT-Llama3-8b.Q3_K_S.gguf | Q3_K_S | 3 | 3.16 GB| 5.66 GB | very small, high quality loss |
+| NorskGPT-Llama3-8b.Q3_K_M.gguf| Q3_K_M | 3 | 3.52 GB| 6.02 GB | very small, high quality loss |
+| NorskGPT-Llama3-8b.Q3_K_L.gguf | Q3_K_L | 3 | 3.82 GB| 6.32 GB | small, substantial quality loss |
+| NorskGPT-Llama3-8b.Q4_0.gguf| Q4_0 | 4 | 4.11 GB| 6.61 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| NorskGPT-Llama3-8b.Q4_K_S.gguf | Q4_K_S | 4 | 4.14 GB| 6.64 GB | small, greater quality loss |
+| NorskGPT-Llama3-8b.Q4_K_M.gguf | Q4_K_M | 4 | 4.37 GB| 6.87 GB | medium, balanced quality - recommended |
+| NorskGPT-Llama3-8b.Q5_0.gguf | Q5_0 | 5 | 5.00 GB| 7.50 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| NorskGPT-Llama3-8b.Q5_K_S.gguf | Q5_K_S | 5 | 5.00 GB| 7.50 GB | large, low quality loss - recommended |
+| NorskGPT-Llama3-8b.Q5_K_M.gguf | Q5_K_M | 5 | 5.13 GB| 7.63 GB | large, very low quality loss - recommended |
+| NorskGPT-Llama3-8b.Q6_K.gguf| Q6_K | 6 | 5.94 GB| 8.44 GB | very large, extremely low quality loss |
+| NorskGPT-Llama3-8b.Q8_0.gguf | Q8_0 | 8 | 7.70 GB| 10.20 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
+
+  Thanks to [TheBloke](https://huggingface.co/TheBloke) for preparing an amazing README on how to use GGUF models