Initial GGML model commit

README.md

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+---
+inference: false
+license: other
+---
+
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+
+# NousResearch's Redmond Hermes Coder GGML
+
+These files are GGML format model files for [NousResearch's Redmond Hermes Coder](https://huggingface.co/NousResearch/Redmond-Hermes-Coder).
+
+GGML files are for CPU + GPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp) and libraries and UIs which support this format, such as:
+* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
+* [KoboldCpp](https://github.com/LostRuins/koboldcpp)
+* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui) using the `c_transformers` backend.
+* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
+* [ctransformers](https://github.com/marella/ctransformers)
+
+## Repositories available
+
+* [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/Redmond-Hermes-Coder-GPTQ)
+* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/Redmond-Hermes-Coder-GGML)
+* [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/NousResearch/Redmond-Hermes-Coder)
+
+## Prompt template: Alpaca
+
+```
+Below is an instruction that describes a task. Write a response that appropriately completes the request.
+
+### Instruction: PROMPT
+
+### Response:
+
+```
+
+<!-- compatibility_ggml start -->
+## Compatibilty
+
+These files are **not** compatible with llama.cpp.
+
+Currently they can be used with:
+* KoboldCpp, a powerful inference engine based on llama.cpp, with good UI: [KoboldCpp](https://github.com/LostRuins/koboldcpp)
+* The ctransformers Python library, which includes LangChain support: [ctransformers](https://github.com/marella/ctransformers)
+* The GPT4All-UI which uses ctransformers: [GPT4All-UI](https://github.com/ParisNeo/gpt4all-ui)
+* [rustformers' llm](https://github.com/rustformers/llm)
+* The example `starcoder` binary provided with [ggml](https://github.com/ggerganov/ggml)
+
+As other options become available I will endeavour to update them here (do let me know in the Community tab if I've missed something!)
+
+## Tutorial for using GPT4All-UI
+
+* [Text tutorial, written by **Lucas3DCG**](https://huggingface.co/TheBloke/MPT-7B-Storywriter-GGML/discussions/2#6475d914e9b57ce0caa68888)
+* [Video tutorial, by GPT4All-UI's author **ParisNeo**](https://www.youtube.com/watch?v=ds_U0TDzbzI)
+<!-- compatibility_ggml end -->
+
+## Provided files
+| Name | Quant method | Bits | Size | Max RAM required | Use case |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+| redmond-hermes-coder.ggmlv3.q4_0.bin | q4_0 | 4 | 10.75 GB| 13.25 GB | 4-bit. |
+| redmond-hermes-coder.ggmlv3.q4_1.bin | q4_1 | 4 | 11.92 GB| 14.42 GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
+| redmond-hermes-coder.ggmlv3.q5_0.bin | q5_0 | 5 | 13.09 GB| 15.59 GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
+| redmond-hermes-coder.ggmlv3.q5_1.bin | q5_1 | 5 | 14.26 GB| 16.76 GB | 5-bit. Even higher accuracy, resource usage and slower inference. |
+| redmond-hermes-coder.ggmlv3.q8_0.bin | q8_0 | 8 | 20.11 GB| 22.61 GB | 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
+
+
+**Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
+
+<!-- footer start -->
+## Discord
+
+For further support, and discussions on these models and AI in general, join us at:
+
+[TheBloke AI's Discord server](https://discord.gg/theblokeai)
+
+## Thanks, and how to contribute.
+
+Thanks to the [chirper.ai](https://chirper.ai) team!
+
+I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
+
+If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
+
+Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.
+
+* Patreon: https://patreon.com/TheBlokeAI
+* Ko-Fi: https://ko-fi.com/TheBlokeAI
+
+**Special thanks to**: Luke from CarbonQuill, Aemon Algiz, Dmitriy Samsonov.
+
+**Patreon special mentions**: zynix , ya boyyy, Trenton Dambrowitz, Imad Khwaja, Alps Aficionado, chris gileta, John Detwiler, Willem Michiel, RoA, Mano Prime, Rainer Wilmers, Fred von Graf, Matthew Berman, Ghost , Nathan LeClaire, Iucharbius , Ai Maven, Illia Dulskyi, Joseph William Delisle, Space Cruiser, Lone Striker, Karl Bernard, Eugene Pentland, Greatston Gnanesh, Jonathan Leane, Randy H, Pierre Kircher, Willian Hasse, Stephen Murray, Alex , terasurfer , Edmond Seymore, Oscar Rangel, Luke Pendergrass, Asp the Wyvern, Junyu Yang, David Flickinger, Luke, Spiking Neurons AB, subjectnull, Pyrater, Nikolai Manek, senxiiz, Ajan Kanaga, Johann-Peter Hartmann, Artur Olbinski, Kevin Schuppel, Derek Yates, Kalila, K, Talal Aujan, Khalefa Al-Ahmad, Gabriel Puliatti, John Villwock, WelcomeToTheClub, Daniel P. Andersen, Preetika Verma, Deep Realms, Fen Risland, trip7s trip, webtim, Sean Connelly, Michael Levine, Chris McCloskey, biorpg, vamX, Viktor Bowallius, Cory Kujawski.
+
+Thank you to all my generous patrons and donaters!
+
+<!-- footer end -->
+
+# Original model card: NousResearch's Redmond Hermes Coder
+
+
+# Model Card: Redmond-Hermes-Coder 15B
+
+## Model Description
+
+Redmond-Hermes-Coder 15B is a state-of-the-art language model fine-tuned on over 300,000 instructions. This model was fine-tuned by Nous Research, with Teknium and Karan4D leading the fine tuning process and dataset curation, Redmond AI sponsoring the compute, and several other contributors.
+
+This model was trained with a WizardCoder base, which itself uses a StarCoder base model. 
+
+The model is truly great at code, but, it does come with a tradeoff though. While far better at code than the original Nous-Hermes built on Llama, it is worse than WizardCoder at pure code benchmarks, like HumanEval.
+
+It comes in at 39% on HumanEval, with WizardCoder at 57%. This is a preliminary experiment, and we are exploring improvements now.
+
+However, it does seem better at non-code than WizardCoder on a variety of things, including writing tasks.
+
+## Model Training
+
+The model was trained almost entirely on synthetic GPT-4 outputs. This includes data from diverse sources such as GPTeacher, the general, roleplay v1&2, code instruct datasets, Nous Instruct & PDACTL (unpublished), CodeAlpaca, Evol_Instruct Uncensored, GPT4-LLM, and Unnatural Instructions. 
+
+Additional data inputs came from Camel-AI's Biology/Physics/Chemistry and Math Datasets, Airoboros' (v1) GPT-4 Dataset, and more from CodeAlpaca. The total volume of data encompassed over 300,000 instructions.
+
+## Collaborators
+The model fine-tuning and the datasets were a collaboration of efforts and resources from members of Nous Research, includingTeknium, Karan4D, Huemin Art, and Redmond AI's generous compute grants. 
+  
+Huge shoutout and acknowledgement is deserved for all the dataset creators who generously share their datasets openly. 
+
+Among the contributors of datasets, GPTeacher was made available by Teknium, Wizard LM by nlpxucan, and the Nous Research Instruct Dataset was provided by Karan4D and HueminArt.  
+The GPT4-LLM and Unnatural Instructions were provided by Microsoft, Airoboros dataset by jondurbin, Camel-AI datasets are from Camel-AI, and CodeAlpaca dataset by Sahil 2801.
+If anyone was left out, please open a thread in the community tab.
+
+## Prompt Format
+
+The model follows the Alpaca prompt format:
+```
+### Instruction:
+
+### Response:
+```
+
+or 
+
+```
+### Instruction:
+
+### Input:
+
+### Response:
+```  
+
+## Resources for Applied Use Cases:
+For an example of a back and forth chatbot using huggingface transformers and discord, check out: https://github.com/teknium1/alpaca-discord  
+For an example of a roleplaying discord bot, check out this: https://github.com/teknium1/alpaca-roleplay-discordbot  
+
+## Future Plans
+The model is currently being uploaded in FP16 format, and there are plans to convert the model to GGML and GPTQ 4bit quantizations. The team is also working on a full benchmark, similar to what was done for GPT4-x-Vicuna. We will try to get in discussions to get the model included in the GPT4All.
+
+## Benchmark Results
+```
+HumanEval: 39%
+|                      Task                      |Version|       Metric        |Value |   |Stderr|
+|------------------------------------------------|------:|---------------------|-----:|---|-----:|
+|arc_challenge                                   |      0|acc                  |0.2858|±  |0.0132|
+|                                                |       |acc_norm             |0.3148|±  |0.0136|
+|arc_easy                                        |      0|acc                  |0.5349|±  |0.0102|
+|                                                |       |acc_norm             |0.5097|±  |0.0103|
+|bigbench_causal_judgement                       |      0|multiple_choice_grade|0.5158|±  |0.0364|
+|bigbench_date_understanding                     |      0|multiple_choice_grade|0.5230|±  |0.0260|
+|bigbench_disambiguation_qa                      |      0|multiple_choice_grade|0.3295|±  |0.0293|
+|bigbench_geometric_shapes                       |      0|multiple_choice_grade|0.1003|±  |0.0159|
+|                                                |       |exact_str_match      |0.0000|±  |0.0000|
+|bigbench_logical_deduction_five_objects         |      0|multiple_choice_grade|0.2260|±  |0.0187|
+|bigbench_logical_deduction_seven_objects        |      0|multiple_choice_grade|0.1957|±  |0.0150|
+|bigbench_logical_deduction_three_objects        |      0|multiple_choice_grade|0.3733|±  |0.0280|
+|bigbench_movie_recommendation                   |      0|multiple_choice_grade|0.3200|±  |0.0209|
+|bigbench_navigate                               |      0|multiple_choice_grade|0.4830|±  |0.0158|
+|bigbench_reasoning_about_colored_objects        |      0|multiple_choice_grade|0.4150|±  |0.0110|
+|bigbench_ruin_names                             |      0|multiple_choice_grade|0.2143|±  |0.0194|
+|bigbench_salient_translation_error_detection    |      0|multiple_choice_grade|0.2926|±  |0.0144|
+|bigbench_snarks                                 |      0|multiple_choice_grade|0.5249|±  |0.0372|
+|bigbench_sports_understanding                   |      0|multiple_choice_grade|0.4817|±  |0.0159|
+|bigbench_temporal_sequences                     |      0|multiple_choice_grade|0.2700|±  |0.0140|
+|bigbench_tracking_shuffled_objects_five_objects |      0|multiple_choice_grade|0.1864|±  |0.0110|
+|bigbench_tracking_shuffled_objects_seven_objects|      0|multiple_choice_grade|0.1349|±  |0.0082|
+|bigbench_tracking_shuffled_objects_three_objects|      0|multiple_choice_grade|0.3733|±  |0.0280|
+|boolq                                           |      1|acc                  |0.5498|±  |0.0087|
+|hellaswag                                       |      0|acc                  |0.3814|±  |0.0048|
+|                                                |       |acc_norm             |0.4677|±  |0.0050|
+|openbookqa                                      |      0|acc                  |0.1960|±  |0.0178|
+|                                                |       |acc_norm             |0.3100|±  |0.0207|
+|piqa                                            |      0|acc                  |0.6600|±  |0.0111|
+|                                                |       |acc_norm             |0.6610|±  |0.0110|
+|winogrande                                      |      0|acc                  |0.5343|±  |0.0140|
+```
+
+## Model Usage
+The model is available for download on Hugging Face. It is suitable for a wide range of language tasks, from generating creative text to understanding and following complex instructions.
+  
+Compute provided by our project sponsor Redmond AI, thank you!!