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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)
+
+
+multimaster-7b-v6 - GGUF
+- Model creator: https://huggingface.co/ibivibiv/
+- Original model: https://huggingface.co/ibivibiv/multimaster-7b-v6/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [multimaster-7b-v6.Q2_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q2_K.gguf) | Q2_K | 12.04GB |
+| [multimaster-7b-v6.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.IQ3_XS.gguf) | IQ3_XS | 13.48GB |
+| [multimaster-7b-v6.IQ3_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.IQ3_S.gguf) | IQ3_S | 14.25GB |
+| [multimaster-7b-v6.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q3_K_S.gguf) | Q3_K_S | 14.23GB |
+| [multimaster-7b-v6.IQ3_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.IQ3_M.gguf) | IQ3_M | 14.49GB |
+| [multimaster-7b-v6.Q3_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q3_K.gguf) | Q3_K | 15.79GB |
+| [multimaster-7b-v6.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q3_K_M.gguf) | Q3_K_M | 15.79GB |
+| [multimaster-7b-v6.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q3_K_L.gguf) | Q3_K_L | 17.1GB |
+| [multimaster-7b-v6.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.IQ4_XS.gguf) | IQ4_XS | 17.79GB |
+| [multimaster-7b-v6.Q4_0.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q4_0.gguf) | Q4_0 | 18.6GB |
+| [multimaster-7b-v6.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.IQ4_NL.gguf) | IQ4_NL | 18.77GB |
+| [multimaster-7b-v6.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q4_K_S.gguf) | Q4_K_S | 18.76GB |
+| [multimaster-7b-v6.Q4_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q4_K.gguf) | Q4_K | 19.96GB |
+| [multimaster-7b-v6.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q4_K_M.gguf) | Q4_K_M | 19.96GB |
+| [multimaster-7b-v6.Q4_1.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q4_1.gguf) | Q4_1 | 20.65GB |
+| [multimaster-7b-v6.Q5_0.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q5_0.gguf) | Q5_0 | 22.7GB |
+| [multimaster-7b-v6.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q5_K_S.gguf) | Q5_K_S | 22.7GB |
+| [multimaster-7b-v6.Q5_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q5_K.gguf) | Q5_K | 23.41GB |
+| [multimaster-7b-v6.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q5_K_M.gguf) | Q5_K_M | 23.41GB |
+| [multimaster-7b-v6.Q5_1.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q5_1.gguf) | Q5_1 | 24.76GB |
+| [multimaster-7b-v6.Q6_K.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q6_K.gguf) | Q6_K | 27.07GB |
+| [multimaster-7b-v6.Q8_0.gguf](https://huggingface.co/RichardErkhov/ibivibiv_-_multimaster-7b-v6-gguf/blob/main/multimaster-7b-v6.Q8_0.gguf) | Q8_0 | 35.06GB |
+
+
+
+
+Original model description:
+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+model-index:
+- name: multimaster-7b-v6
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 72.78
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ibivibiv/multimaster-7b-v6
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 88.77
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ibivibiv/multimaster-7b-v6
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 64.74
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ibivibiv/multimaster-7b-v6
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 70.89
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ibivibiv/multimaster-7b-v6
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 86.42
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ibivibiv/multimaster-7b-v6
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 70.36
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ibivibiv/multimaster-7b-v6
+      name: Open LLM Leaderboard
+---
+
+# Multi Master 7Bx5 v6
+
+![img](./multimaster.png)
+
+A quick multi-disciplinary moe model.  This is part of a series of models built to test the gate tuning for mixtral style moe models.
+
+# Prompting
+
+## Prompt Template for alpaca style
+
+```
+### Instruction:
+
+<prompt> (without the <>)
+
+### Response:
+```
+
+## Sample Code
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+torch.set_default_device("cuda")
+
+model = AutoModelForCausalLM.from_pretrained("ibivibiv/multimaster-7b-v6", torch_dtype="auto", device_config='auto')
+tokenizer = AutoTokenizer.from_pretrained("ibivibiv/multimaster-7b-v6")
+
+inputs = tokenizer("### Instruction: Who would when in an arm wrestling match between Abraham Lincoln and Chuck Norris?\nA. Abraham Lincoln \nB. Chuck Norris\n### Response:\n", return_tensors="pt", return_attention_mask=False)
+
+outputs = model.generate(**inputs, max_length=200)
+text = tokenizer.batch_decode(outputs)[0]
+print(text)
+```
+
+# Model Details
+* **Trained by**: [ibivibiv](https://huggingface.co/ibivibiv)
+* **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers)
+* **Model type:**  **multimaster-7b** is a lora tuned version of openchat/openchat-3.5-0106 with the adapter merged back into the main model
+* **Language(s)**: English
+* **Purpose**: This model is a focus on multi-disciplinary model tuning
+
+# Benchmark Scores
+
+coming soon
+
+## Citations
+
+```
+@misc{open-llm-leaderboard,
+  author = {Edward Beeching and Clémentine Fourrier and Nathan Habib and Sheon Han and Nathan Lambert and Nazneen Rajani and Omar Sanseviero and Lewis Tunstall and Thomas Wolf},
+  title = {Open LLM Leaderboard},
+  year = {2023},
+  publisher = {Hugging Face},
+  howpublished = "\url{https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard}"
+}
+```
+```
+@software{eval-harness,
+  author       = {Gao, Leo and
+                  Tow, Jonathan and
+                  Biderman, Stella and
+                  Black, Sid and
+                  DiPofi, Anthony and
+                  Foster, Charles and
+                  Golding, Laurence and
+                  Hsu, Jeffrey and
+                  McDonell, Kyle and
+                  Muennighoff, Niklas and
+                  Phang, Jason and
+                  Reynolds, Laria and
+                  Tang, Eric and
+                  Thite, Anish and
+                  Wang, Ben and
+                  Wang, Kevin and
+                  Zou, Andy},
+  title        = {A framework for few-shot language model evaluation},
+  month        = sep,
+  year         = 2021,
+  publisher    = {Zenodo},
+  version      = {v0.0.1},
+  doi          = {10.5281/zenodo.5371628},
+  url          = {https://doi.org/10.5281/zenodo.5371628}
+}
+```
+```
+@misc{clark2018think,
+      title={Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},
+      author={Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},
+      year={2018},
+      eprint={1803.05457},
+      archivePrefix={arXiv},
+      primaryClass={cs.AI}
+}
+```
+```
+@misc{zellers2019hellaswag,
+      title={HellaSwag: Can a Machine Really Finish Your Sentence?},
+      author={Rowan Zellers and Ari Holtzman and Yonatan Bisk and Ali Farhadi and Yejin Choi},
+      year={2019},
+      eprint={1905.07830},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+```
+@misc{hendrycks2021measuring,
+      title={Measuring Massive Multitask Language Understanding},
+      author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt},
+      year={2021},
+      eprint={2009.03300},
+      archivePrefix={arXiv},
+      primaryClass={cs.CY}
+}
+```
+```
+@misc{lin2022truthfulqa,
+      title={TruthfulQA: Measuring How Models Mimic Human Falsehoods},
+      author={Stephanie Lin and Jacob Hilton and Owain Evans},
+      year={2022},
+      eprint={2109.07958},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+```
+@misc{DBLP:journals/corr/abs-1907-10641,
+      title={{WINOGRANDE:} An Adversarial Winograd Schema Challenge at Scale},
+      author={Keisuke Sakaguchi and Ronan Le Bras and Chandra Bhagavatula and Yejin Choi},
+      year={2019},
+      eprint={1907.10641},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+```
+@misc{DBLP:journals/corr/abs-2110-14168,
+      title={Training Verifiers to Solve Math Word Problems},
+      author={Karl Cobbe and
+                  Vineet Kosaraju and
+                  Mohammad Bavarian and
+                  Mark Chen and
+                  Heewoo Jun and
+                  Lukasz Kaiser and
+                  Matthias Plappert and
+                  Jerry Tworek and
+                  Jacob Hilton and
+                  Reiichiro Nakano and
+                  Christopher Hesse and
+                  John Schulman},
+      year={2021},
+      eprint={2110.14168},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ibivibiv__multimaster-7b-v6)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |75.66|
+|AI2 Reasoning Challenge (25-Shot)|72.78|
+|HellaSwag (10-Shot)              |88.77|
+|MMLU (5-Shot)                    |64.74|
+|TruthfulQA (0-shot)              |70.89|
+|Winogrande (5-shot)              |86.42|
+|GSM8k (5-shot)                   |70.36|
+
+
+