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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+Yarn-Mistral-7b-128k-sharded - GGUF
+- Model creator: https://huggingface.co/yanismiraoui/
+- Original model: https://huggingface.co/yanismiraoui/Yarn-Mistral-7b-128k-sharded/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [Yarn-Mistral-7b-128k-sharded.Q2_K.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q2_K.gguf) | Q2_K | 2.53GB |
+| [Yarn-Mistral-7b-128k-sharded.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.IQ3_XS.gguf) | IQ3_XS | 0.34GB |
+| [Yarn-Mistral-7b-128k-sharded.IQ3_S.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.IQ3_S.gguf) | IQ3_S | 0.05GB |
+| [Yarn-Mistral-7b-128k-sharded.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q3_K_S.gguf) | Q3_K_S | 0.03GB |
+| [Yarn-Mistral-7b-128k-sharded.IQ3_M.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.IQ3_M.gguf) | IQ3_M | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q3_K.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q3_K.gguf) | Q3_K | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q3_K_M.gguf) | Q3_K_M | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q3_K_L.gguf) | Q3_K_L | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.IQ4_XS.gguf) | IQ4_XS | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q4_0.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q4_0.gguf) | Q4_0 | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.IQ4_NL.gguf) | IQ4_NL | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q4_K_S.gguf) | Q4_K_S | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q4_K.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q4_K.gguf) | Q4_K | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q4_K_M.gguf) | Q4_K_M | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q4_1.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q4_1.gguf) | Q4_1 | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q5_0.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q5_0.gguf) | Q5_0 | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q5_K_S.gguf) | Q5_K_S | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q5_K.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q5_K.gguf) | Q5_K | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q5_K_M.gguf) | Q5_K_M | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q5_1.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q5_1.gguf) | Q5_1 | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q6_K.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q6_K.gguf) | Q6_K | 0.0GB |
+| [Yarn-Mistral-7b-128k-sharded.Q8_0.gguf](https://huggingface.co/RichardErkhov/yanismiraoui_-_Yarn-Mistral-7b-128k-sharded-gguf/blob/main/Yarn-Mistral-7b-128k-sharded.Q8_0.gguf) | Q8_0 | 0.0GB |
+
+
+
+
+Original model description:
+---
+datasets:
+- emozilla/yarn-train-tokenized-16k-mistral
+metrics:
+- perplexity
+library_name: transformers
+license: apache-2.0
+language:
+- en
+---
+
+
+## This repo contains a SHARDED version of: https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k
+
+### Huge thanks to the publishers for their amazing work, all credits go to them: https://huggingface.co/NousResearch
+
+# Model Card: Nous-Yarn-Mistral-7b-128k
+
+[Preprint (arXiv)](https://arxiv.org/abs/2309.00071)  
+[GitHub](https://github.com/jquesnelle/yarn)
+![yarn](https://raw.githubusercontent.com/jquesnelle/yarn/mistral/data/proofpile-long-small-mistral.csv.png)
+
+## Model Description
+
+Nous-Yarn-Mistral-7b-128k is a state-of-the-art language model for long context, further pretrained on long context data for 1500 steps using the YaRN extension method.
+It is an extension of [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) and supports a 128k token context window.
+
+To use, pass `trust_remote_code=True` when loading the model, for example
+
+```python
+model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Mistral-7b-128k",
+  use_flash_attention_2=True,
+  torch_dtype=torch.bfloat16,
+  device_map="auto",
+  trust_remote_code=True)
+```
+
+In addition you will need to use the latest version of `transformers` (until 4.35 comes out)
+```sh
+pip install git+https://github.com/huggingface/transformers
+```
+
+## Benchmarks
+
+Long context benchmarks:
+| Model | Context Window | 8k PPL | 16k PPL | 32k PPL | 64k PPL | 128k PPL |
+|-------|---------------:|------:|----------:|-----:|-----:|------------:|
+| [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 8k | 2.96 | - | - | - | - |
+| [Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) | 64k | 3.04 | 2.65 | 2.44 | 2.20 | - |
+| [Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k) | 128k | 3.08 | 2.68 | 2.47 | 2.24 | 2.19 |
+
+Short context benchmarks showing that quality degradation is minimal:
+| Model | Context Window | ARC-c | Hellaswag | MMLU | Truthful QA |
+|-------|---------------:|------:|----------:|-----:|------------:|
+| [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 8k | 59.98 | 83.31 | 64.16 | 42.15 |
+| [Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) | 64k | 59.38 | 81.21 | 61.32 | 42.50 |
+| [Yarn-Mistral-7b-128k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k) | 128k | 58.87 | 80.58 | 60.64 | 42.46 |
+
+## Collaborators
+
+ - [bloc97](https://github.com/bloc97): Methods, paper and evals
+ - [@theemozilla](https://twitter.com/theemozilla): Methods, paper, model training, and evals
+ - [@EnricoShippole](https://twitter.com/EnricoShippole): Model training
+ - [honglu2875](https://github.com/honglu2875): Paper and evals
+
+The authors would like to thank LAION AI for their support of compute for this model.
+It was trained on the [JUWELS](https://www.fz-juelich.de/en/ias/jsc/systems/supercomputers/juwels) supercomputer.
+