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Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B-GGUF

Text Generation
Transformers
GGUF
Safetensors
mistral
quantized
2-bit
3-bit
4-bit precision
5-bit
6-bit
8-bit precision
GGUF
Merge
mergekit
lazymergekit
automerger
Inference Endpoints
text-generation-inference
Model card Files Community
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+ ---
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+ tags:
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+ - quantized
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+ - 2-bit
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+ - 3-bit
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+ - 4-bit
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+ - 5-bit
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+ - 6-bit
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+ - 8-bit
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+ - GGUF
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+ - transformers
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+ - safetensors
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+ - mistral
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+ - text-generation
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+ - merge
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+ - mergekit
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+ - lazymergekit
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+ - automerger
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+ - base_model:MaziyarPanahi/MeliodasPercival_01_Experiment26T3q
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+ - license:apache-2.0
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+ - autotrain_compatible
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+ - endpoints_compatible
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+ - text-generation-inference
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+ - region:us
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+ - text-generation
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+ model_name: Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B-GGUF
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+ base_model: automerger/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B
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+ inference: false
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+ model_creator: automerger
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+ pipeline_tag: text-generation
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+ quantized_by: MaziyarPanahi
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+ ---
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+ # [MaziyarPanahi/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B-GGUF](https://huggingface.co/MaziyarPanahi/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B-GGUF)
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+ - Model creator: [automerger](https://huggingface.co/automerger)
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+ - Original model: [automerger/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B](https://huggingface.co/automerger/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B)
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+
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+ ## Description
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+ [MaziyarPanahi/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B-GGUF](https://huggingface.co/MaziyarPanahi/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B-GGUF) contains GGUF format model files for [automerger/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B](https://huggingface.co/automerger/Ognoexperiment27multi_verse_modelMeliodaspercival_01_experiment26t3q-7B).
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+
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+ ### About GGUF
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+
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+ GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.
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+
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+ Here is an incomplete list of clients and libraries that are known to support GGUF:
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+
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+ * [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option.
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+ * [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
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+ * [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
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+ * [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
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+ * [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
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+ * [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
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+ * [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
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+ * [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
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+ * [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
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+ * [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models.
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+
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+ ## Special thanks
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+
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+ 🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.