| Quantization made by Richard Erkhov. | |
| [Github](https://github.com/RichardErkhov) | |
| [Discord](https://discord.gg/pvy7H8DZMG) | |
| [Request more models](https://github.com/RichardErkhov/quant_request) | |
| MoMo-72B-LoRA-V1.4 - GGUF | |
| - Model creator: https://huggingface.co/moreh/ | |
| - Original model: https://huggingface.co/moreh/MoMo-72B-LoRA-V1.4/ | |
| | Name | Quant method | Size | | |
| | ---- | ---- | ---- | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| | [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 | | |
| Original model description: | |
| --- | |
| license: mit | |
| language: | |
| - en | |
| --- | |
| # **Introduction** | |
| 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. | |
| Note that we did not exploit any form of weight merge. | |
| For leaderboard submission, the trained weight is realigned for compatibility with llama. | |
| 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. | |
| ## Details | |
| ### Used Librarys | |
| - torch | |
| - peft | |
| ### Used Datasets | |
| - Open-Orca/SlimOrca | |
| - No other dataset was used | |
| - No benchmark test set or the training set are used | |
| - [data contamination check](https://github.com/swj0419/detect-pretrain-code-contamination) result | |
| | Model | ARC | MMLU | TruthfulQA | GSM8K | | |
| |------------------------------|-------|-------|-------|-------| | |
| | **V1.4(result < 0.1, %)**| TBU |0.73 | 0.71 | TBU | | |
| ### Used Environments | |
| - AMD MI250 & MoAI platform | |
| - Please visit https://moreh.io/product for more information about MoAI platform | |
| - Or, contact us directly [[email protected]](mailto:[email protected]) | |
| ## How to use | |
| ```python | |
| # pip install transformers==4.35.2 | |
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| tokenizer = AutoTokenizer.from_pretrained("moreh/MoMo-72B-LoRA-V1.4") | |
| model = AutoModelForCausalLM.from_pretrained( | |
| "moreh/MoMo-72B-LoRA-V1.4" | |
| ) | |
| ``` | |