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Browse files- README.md +42 -0
- config.json +38 -0
- huggingface-metadata.txt +15 -0
- model.safetensors.index.json +1 -0
- output-00001-of-00002.safetensors +3 -0
- output-00002-of-00002.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
README.md
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---
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base_model:
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- unsloth/Mistral-Small-Instruct-2409
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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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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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# MS-Meadowlark-22B
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<figure>
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<img src="https://huggingface.co/ToastyPigeon/MS-Meadowlark-22B/resolve/main/00036-141420187-3.png" width="750">
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<figcaption>Big thanks to @inflatebot for the image.</figcaption>
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</figure>
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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](https://huggingface.co/datasets/Dampfinchen/Creative_Writing_Multiturn) at 16k
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- [Fizzarolli/rosier-dataset](https://huggingface.co/datasets/Fizzarolli/rosier-dataset) + [Alfitaria/body-inflation-org](https://huggingface.co/datasets/Alfitaria/body-inflation-org) at 16k
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- [ToastyPigeon/SpringDragon](https://huggingface.co/datasets/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](https://huggingface.co/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](https://lite.koboldai.net/) 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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```
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<s>[INST] {User message}[/INST] {Assistant response}</s>
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```
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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](https://huggingface.co/ToastyPigeon/ST-Presets-Mistral-Small) 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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config.json
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{
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"_name_or_path": "unsloth/Mistral-Small-Instruct-2409",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 6144,
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"initializer_range": 0.02,
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"intermediate_size": 16384,
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"max_position_embeddings": 131072,
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"model_type": "mistral",
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"num_attention_heads": 48,
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"num_hidden_layers": 56,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.43.3",
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"use_cache": true,
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"vocab_size": 32768,
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"quantization_config": {
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"quant_method": "exl2",
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"version": "0.2.3",
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"bits": 4.0,
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"head_bits": 6,
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"calibration": {
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"rows": 115,
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"length": 2048,
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"dataset": "(default)"
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}
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}
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}
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huggingface-metadata.txt
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url: https://huggingface.co/allura-org/MS-Meadowlark-22B
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branch: main
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download date: 2024-11-19 09:20:35
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