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moreh_-_MoMo-72B-LoRA-V1.4-gguf

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+ Quantization made by Richard Erkhov.
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+ [Github](https://github.com/RichardErkhov)
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+ [Discord](https://discord.gg/pvy7H8DZMG)
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+
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+ [Request more models](https://github.com/RichardErkhov/quant_request)
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+
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+ MoMo-72B-LoRA-V1.4 - GGUF
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+ - Model creator: https://huggingface.co/moreh/
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+ - Original model: https://huggingface.co/moreh/MoMo-72B-LoRA-V1.4/
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+
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+
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+ | Name | Quant method | Size |
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+ | ---- | ---- | ---- |
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+ | [MoMo-72B-LoRA-V1.4.Q2_K.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.Q2_K.gguf) | Q2_K | 25.22GB |
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+ | [MoMo-72B-LoRA-V1.4.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.IQ3_XS.gguf) | IQ3_XS | 27.88GB |
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+ | [MoMo-72B-LoRA-V1.4.IQ3_S.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.IQ3_S.gguf) | IQ3_S | 29.4GB |
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+ | [MoMo-72B-LoRA-V1.4.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.Q3_K_S.gguf) | Q3_K_S | 29.4GB |
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+ | [MoMo-72B-LoRA-V1.4.IQ3_M.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.IQ3_M.gguf) | IQ3_M | 30.98GB |
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+ | [MoMo-72B-LoRA-V1.4.Q3_K.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.Q3_K.gguf) | Q3_K | 32.85GB |
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+ | [MoMo-72B-LoRA-V1.4.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.Q3_K_M.gguf) | Q3_K_M | 32.85GB |
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+ | [MoMo-72B-LoRA-V1.4.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.Q3_K_L.gguf) | Q3_K_L | 35.85GB |
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+ | [MoMo-72B-LoRA-V1.4.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/blob/main/MoMo-72B-LoRA-V1.4.IQ4_XS.gguf) | IQ4_XS | 36.41GB |
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+ | [MoMo-72B-LoRA-V1.4.Q4_0.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q4_0 | 38.19GB |
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+ | [MoMo-72B-LoRA-V1.4.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | IQ4_NL | 38.42GB |
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+ | [MoMo-72B-LoRA-V1.4.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q4_K_S | 38.45GB |
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+ | [MoMo-72B-LoRA-V1.4.Q4_K.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q4_K | 40.77GB |
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+ | [MoMo-72B-LoRA-V1.4.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q4_K_M | 40.77GB |
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+ | [MoMo-72B-LoRA-V1.4.Q4_1.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q4_1 | 42.32GB |
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+ | [MoMo-72B-LoRA-V1.4.Q5_0.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q5_0 | 46.46GB |
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+ | [MoMo-72B-LoRA-V1.4.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q5_K_S | 46.46GB |
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+ | [MoMo-72B-LoRA-V1.4.Q5_K.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q5_K | 47.79GB |
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+ | [MoMo-72B-LoRA-V1.4.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q5_K_M | 47.79GB |
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+ | [MoMo-72B-LoRA-V1.4.Q5_1.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q5_1 | 50.59GB |
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+ | [MoMo-72B-LoRA-V1.4.Q6_K.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q6_K | 55.24GB |
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+ | [MoMo-72B-LoRA-V1.4.Q8_0.gguf](https://huggingface.co/RichardErkhov/moreh_-_MoMo-72B-LoRA-V1.4-gguf/tree/main/) | Q8_0 | 71.55GB |
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+
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+
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+
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+ Original model description:
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+ ---
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+ license: mit
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+ language:
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+ - en
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+ ---
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+ # **Introduction**
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+ MoMo-72B is trained via Supervised Fine-Tuning (SFT) using [LoRA](https://arxiv.org/abs/2106.09685), with the QWEN-72B model as its base-model.
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+ Note that we did not exploit any form of weight merge.
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+ For leaderboard submission, the trained weight is realigned for compatibility with llama.
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+ MoMo-72B is trained using **[Moreh](https://moreh.io/)**'s [MoAI platform](https://moreh.io/product), which simplifies the training of large-scale models, and AMD's MI250 GPU.
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+
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+
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+ ## Details
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+ ### Used Librarys
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+ - torch
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+ - peft
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+ ### Used Datasets
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+ - Open-Orca/SlimOrca
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+ - No other dataset was used
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+ - No benchmark test set or the training set are used
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+ - [data contamination check](https://github.com/swj0419/detect-pretrain-code-contamination) result
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+
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+ | Model | ARC | MMLU | TruthfulQA | GSM8K |
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+ |------------------------------|-------|-------|-------|-------|
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+ | **V1.4(result < 0.1, %)**| TBU |0.73 | 0.71 | TBU |
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+ ### Used Environments
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+ - AMD MI250 & MoAI platform
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+ - Please visit https://moreh.io/product for more information about MoAI platform
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+ - Or, contact us directly [[email protected]](mailto:[email protected])
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+
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+ ## How to use
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+
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+ ```python
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+ # pip install transformers==4.35.2
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ tokenizer = AutoTokenizer.from_pretrained("moreh/MoMo-72B-LoRA-V1.4")
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "moreh/MoMo-72B-LoRA-V1.4"
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+ )
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+ ```
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+