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.