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--- |
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base_model: allura-org/MS-Meadowlark-22B |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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- llama-cpp |
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- gguf-my-repo |
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license: other |
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license_name: mrl |
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license_link: https://mistral.ai/licenses/MRL-0.1.md |
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--- |
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# Triangle104/MS-Meadowlark-22B-Q4_K_M-GGUF |
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This model was converted to GGUF format from [`allura-org/MS-Meadowlark-22B`](https://huggingface.co/allura-org/MS-Meadowlark-22B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
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Refer to the [original model card](https://huggingface.co/allura-org/MS-Meadowlark-22B) for more details on the model. |
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Model details: |
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- |
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A roleplay and storywriting model based on Mistral Small 22B. |
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GGUF models: https://huggingface.co/mradermacher/MS-Meadowlark-22B-GGUF/ |
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EXL2 models: https://huggingface.co/CalamitousFelicitousness/MS-Meadowlark-22B-exl2 |
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Datasets used in this model: |
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Dampfinchen/Creative_Writing_Multiturn at 16k |
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Fizzarolli/rosier-dataset + Alfitaria/body-inflation-org at 16k |
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ToastyPigeon/SpringDragon at 8k |
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Each dataset was trained separately onto Mistral Small Instruct, and then the component models were merged along with nbeerbower/Mistral-Small-Gutenberg-Doppel-22B to create Meadowlark. |
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I tried different blends of the component models, and this one seems to be the most stable while retaining creativity and unpredictability added by the trained data. |
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Instruct Format |
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Rosier/bodyinf and SpringDragon were trained in completion format. This model should work with Kobold Lite in Adventure Mode and Story Mode. |
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Creative_Writing_Multiturn and Gutenberg-Doppel were trained using the official instruct format of Mistral Small Instruct: |
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<s>[INST] {User message}[/INST] {Assistant response}</s> |
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This is the Mistral Small V2&V3 preset in SillyTavern and Kobold Lite. |
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For SillyTavern in particular I've had better luck getting good output from Mistral Small using a custom instruct template that formats the assembled context as a single user turn. This prevents SillyTavern from confusing the model by assembling user/assistant turns in a nonstandard way. Note: This preset is not compatible with Stepped Thinking, use the Mistral V2&V3 preset for that. |
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--- |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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llama-cli --hf-repo Triangle104/MS-Meadowlark-22B-Q4_K_M-GGUF --hf-file ms-meadowlark-22b-q4_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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### Server: |
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```bash |
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llama-server --hf-repo Triangle104/MS-Meadowlark-22B-Q4_K_M-GGUF --hf-file ms-meadowlark-22b-q4_k_m.gguf -c 2048 |
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``` |
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo Triangle104/MS-Meadowlark-22B-Q4_K_M-GGUF --hf-file ms-meadowlark-22b-q4_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo Triangle104/MS-Meadowlark-22B-Q4_K_M-GGUF --hf-file ms-meadowlark-22b-q4_k_m.gguf -c 2048 |
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``` |
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