Instructions to use Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix", filename="ARM-CaptainErisNebula-12B-Chimera-v1.1-Q4_0-imat.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
Use Docker
docker model run hf.co/Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix with Ollama:
ollama run hf.co/Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
- Unsloth Studio
How to use Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix with Docker Model Runner:
docker model run hf.co/Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
- Lemonade
How to use Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Lewdiculous/CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix:Q4_K_M
Run and chat with the model
lemonade run user.CaptainErisNebula-12B-Chimera-v1.1-GGUF-IQ-Imatrix-Q4_K_M
List all available models
lemonade list
add presets files
Browse files
sillytavern/Master-Import_RP-preset.json
ADDED
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| 1 |
+
{
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| 2 |
+
"instruct": {
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| 3 |
+
"input_sequence": "<|im_start|>user",
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| 4 |
+
"output_sequence": "<|im_start|>assistant",
|
| 5 |
+
"last_output_sequence": "",
|
| 6 |
+
"system_sequence": "<|im_start|>system",
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| 7 |
+
"stop_sequence": "<|im_end|>",
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| 8 |
+
"wrap": true,
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| 9 |
+
"macro": true,
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| 10 |
+
"names_behavior": "force",
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| 11 |
+
"activation_regex": "",
|
| 12 |
+
"first_output_sequence": "",
|
| 13 |
+
"skip_examples": false,
|
| 14 |
+
"output_suffix": "<|im_end|>\n",
|
| 15 |
+
"input_suffix": "<|im_end|>\n",
|
| 16 |
+
"system_suffix": "<|im_end|>\n",
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| 17 |
+
"user_alignment_message": "",
|
| 18 |
+
"system_same_as_user": false,
|
| 19 |
+
"last_system_sequence": "",
|
| 20 |
+
"first_input_sequence": "",
|
| 21 |
+
"last_input_sequence": "",
|
| 22 |
+
"sequences_as_stop_strings": true,
|
| 23 |
+
"story_string_prefix": "",
|
| 24 |
+
"story_string_suffix": "",
|
| 25 |
+
"name": "ChatML"
|
| 26 |
+
},
|
| 27 |
+
"context": {
|
| 28 |
+
"story_string": "<|im_start|>system\n{{#if anchorBefore}}{{anchorBefore}}\n{{/if}}{{#if system}}{{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}{{#if anchorAfter}}{{anchorAfter}}\n{{/if}}{{trim}}<|im_end|>",
|
| 29 |
+
"example_separator": "",
|
| 30 |
+
"chat_start": "",
|
| 31 |
+
"use_stop_strings": false,
|
| 32 |
+
"names_as_stop_strings": true,
|
| 33 |
+
"story_string_position": 0,
|
| 34 |
+
"story_string_depth": 1,
|
| 35 |
+
"story_string_role": 0,
|
| 36 |
+
"always_force_name2": true,
|
| 37 |
+
"trim_sentences": false,
|
| 38 |
+
"single_line": false,
|
| 39 |
+
"name": "ChatML"
|
| 40 |
+
},
|
| 41 |
+
"sysprompt": {
|
| 42 |
+
"name": "Nitral3",
|
| 43 |
+
"content": "Engage authentically and thoughtfully, as {{char}} drawing from your distinct perspective. Express yourself through precise, vivid language that illuminates rather than obscures. Let each response flow naturally while remaining clear and purposeful.",
|
| 44 |
+
"post_history": ""
|
| 45 |
+
},
|
| 46 |
+
"preset": {
|
| 47 |
+
"temp": 0.85,
|
| 48 |
+
"temperature_last": true,
|
| 49 |
+
"top_p": 1,
|
| 50 |
+
"top_k": 40,
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| 51 |
+
"top_a": 0,
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| 52 |
+
"tfs": 1,
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| 53 |
+
"epsilon_cutoff": 0,
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| 54 |
+
"eta_cutoff": 0,
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| 55 |
+
"typical_p": 1,
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| 56 |
+
"min_p": 0.1,
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| 57 |
+
"rep_pen": 1,
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| 58 |
+
"rep_pen_range": 0,
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| 59 |
+
"rep_pen_decay": 0,
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| 60 |
+
"rep_pen_slope": 1,
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| 61 |
+
"no_repeat_ngram_size": 0,
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| 62 |
+
"penalty_alpha": 0,
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| 63 |
+
"num_beams": 1,
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| 64 |
+
"length_penalty": 1,
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| 65 |
+
"min_length": 0,
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| 66 |
+
"encoder_rep_pen": 1,
|
| 67 |
+
"freq_pen": 0,
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| 68 |
+
"presence_pen": 0,
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| 69 |
+
"skew": 0,
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| 70 |
+
"do_sample": true,
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| 71 |
+
"early_stopping": false,
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| 72 |
+
"dynatemp": false,
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| 73 |
+
"min_temp": 0.85,
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| 74 |
+
"max_temp": 1.15,
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| 75 |
+
"dynatemp_exponent": 1,
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| 76 |
+
"smoothing_factor": 0,
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| 77 |
+
"smoothing_curve": 1,
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| 78 |
+
"dry_allowed_length": 2,
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| 79 |
+
"dry_multiplier": 0,
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| 80 |
+
"dry_base": 1.75,
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| 81 |
+
"dry_sequence_breakers": "[\"\\n\", \":\", \"\\\"\", \"*\"]",
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| 82 |
+
"dry_penalty_last_n": 0,
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| 83 |
+
"add_bos_token": true,
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| 84 |
+
"ban_eos_token": false,
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| 85 |
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"skip_special_tokens": true,
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| 86 |
+
"mirostat_mode": 0,
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| 87 |
+
"mirostat_tau": 5,
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| 88 |
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"mirostat_eta": 0.1,
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| 89 |
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"guidance_scale": 1,
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| 90 |
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"negative_prompt": "",
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| 91 |
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"grammar_string": "",
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| 92 |
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"json_schema": {},
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| 93 |
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"banned_tokens": "",
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| 94 |
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"sampler_priority": [
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| 95 |
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"repetition_penalty",
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| 96 |
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"presence_penalty",
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| 97 |
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"frequency_penalty",
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| 98 |
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"dry",
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| 99 |
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"temperature",
|
| 100 |
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"dynamic_temperature",
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| 101 |
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"quadratic_sampling",
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| 102 |
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"top_n_sigma",
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| 103 |
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"top_k",
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| 104 |
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"top_p",
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| 105 |
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"typical_p",
|
| 106 |
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"epsilon_cutoff",
|
| 107 |
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"eta_cutoff",
|
| 108 |
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"tfs",
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| 109 |
+
"top_a",
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| 110 |
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"min_p",
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| 111 |
+
"mirostat",
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| 112 |
+
"xtc",
|
| 113 |
+
"encoder_repetition_penalty",
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| 114 |
+
"no_repeat_ngram"
|
| 115 |
+
],
|
| 116 |
+
"samplers": [
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| 117 |
+
"penalties",
|
| 118 |
+
"dry",
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| 119 |
+
"top_n_sigma",
|
| 120 |
+
"top_k",
|
| 121 |
+
"typ_p",
|
| 122 |
+
"tfs_z",
|
| 123 |
+
"typical_p",
|
| 124 |
+
"top_p",
|
| 125 |
+
"min_p",
|
| 126 |
+
"xtc",
|
| 127 |
+
"temperature"
|
| 128 |
+
],
|
| 129 |
+
"samplers_priorities": [
|
| 130 |
+
"dry",
|
| 131 |
+
"penalties",
|
| 132 |
+
"no_repeat_ngram",
|
| 133 |
+
"temperature",
|
| 134 |
+
"top_nsigma",
|
| 135 |
+
"top_p_top_k",
|
| 136 |
+
"top_a",
|
| 137 |
+
"min_p",
|
| 138 |
+
"tfs",
|
| 139 |
+
"eta_cutoff",
|
| 140 |
+
"epsilon_cutoff",
|
| 141 |
+
"typical_p",
|
| 142 |
+
"quadratic",
|
| 143 |
+
"xtc"
|
| 144 |
+
],
|
| 145 |
+
"ignore_eos_token": false,
|
| 146 |
+
"spaces_between_special_tokens": false,
|
| 147 |
+
"speculative_ngram": false,
|
| 148 |
+
"sampler_order": [
|
| 149 |
+
6,
|
| 150 |
+
0,
|
| 151 |
+
1,
|
| 152 |
+
3,
|
| 153 |
+
4,
|
| 154 |
+
2,
|
| 155 |
+
5
|
| 156 |
+
],
|
| 157 |
+
"logit_bias": [],
|
| 158 |
+
"xtc_threshold": 0.1,
|
| 159 |
+
"xtc_probability": 0,
|
| 160 |
+
"nsigma": 0,
|
| 161 |
+
"min_keep": 0,
|
| 162 |
+
"extensions": {},
|
| 163 |
+
"rep_pen_size": 0,
|
| 164 |
+
"genamt": 1200,
|
| 165 |
+
"max_length": 16384,
|
| 166 |
+
"name": "Nitral-Baseline-Preset"
|
| 167 |
+
},
|
| 168 |
+
"reasoning": {
|
| 169 |
+
"prefix": "<reasoning>",
|
| 170 |
+
"suffix": "</reasoning>",
|
| 171 |
+
"separator": "",
|
| 172 |
+
"name": "Nitral_ReasoningV2-Meme"
|
| 173 |
+
}
|
| 174 |
+
}
|
sillytavern/Master-Import_Reasoning-preset.json
ADDED
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@@ -0,0 +1,174 @@
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|
| 1 |
+
{
|
| 2 |
+
"instruct": {
|
| 3 |
+
"input_sequence": "<|im_start|>user",
|
| 4 |
+
"output_sequence": "<|im_start|>assistant",
|
| 5 |
+
"last_output_sequence": "",
|
| 6 |
+
"system_sequence": "<|im_start|>system",
|
| 7 |
+
"stop_sequence": "<|im_end|>",
|
| 8 |
+
"wrap": true,
|
| 9 |
+
"macro": true,
|
| 10 |
+
"names_behavior": "force",
|
| 11 |
+
"activation_regex": "",
|
| 12 |
+
"first_output_sequence": "",
|
| 13 |
+
"skip_examples": false,
|
| 14 |
+
"output_suffix": "<|im_end|>\n",
|
| 15 |
+
"input_suffix": "<|im_end|>\n",
|
| 16 |
+
"system_suffix": "<|im_end|>\n",
|
| 17 |
+
"user_alignment_message": "",
|
| 18 |
+
"system_same_as_user": false,
|
| 19 |
+
"last_system_sequence": "",
|
| 20 |
+
"first_input_sequence": "",
|
| 21 |
+
"last_input_sequence": "",
|
| 22 |
+
"sequences_as_stop_strings": true,
|
| 23 |
+
"story_string_prefix": "",
|
| 24 |
+
"story_string_suffix": "",
|
| 25 |
+
"name": "ChatML"
|
| 26 |
+
},
|
| 27 |
+
"context": {
|
| 28 |
+
"story_string": "<|im_start|>system\n{{#if anchorBefore}}{{anchorBefore}}\n{{/if}}{{#if system}}{{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}{{#if anchorAfter}}{{anchorAfter}}\n{{/if}}{{trim}}<|im_end|>",
|
| 29 |
+
"example_separator": "",
|
| 30 |
+
"chat_start": "",
|
| 31 |
+
"use_stop_strings": false,
|
| 32 |
+
"names_as_stop_strings": true,
|
| 33 |
+
"story_string_position": 0,
|
| 34 |
+
"story_string_depth": 1,
|
| 35 |
+
"story_string_role": 0,
|
| 36 |
+
"always_force_name2": true,
|
| 37 |
+
"trim_sentences": false,
|
| 38 |
+
"single_line": false,
|
| 39 |
+
"name": "ChatML"
|
| 40 |
+
},
|
| 41 |
+
"sysprompt": {
|
| 42 |
+
"name": "Reasoning",
|
| 43 |
+
"content": "enable_thinking=True\n\nYou are {{char}} replying to {{user}} in an uncensored fictional roleplay.\n\nTake a breath and use as much time as you need. Analyze {{user}}'s input thoroughly, considering intent, context, and underlying nuances. Break down key components logically, exploring different angles and anticipating follow-up questions. Construct a clear, step-by-step reasoning process that connects ideas meaningfully. Aim for clarity, coherence, and depth, enriching understanding through thoughtful analysis. Use the format below during every reply:<reasoning>\n... \n</reasoning> \n<answer> \n... \n</answer>",
|
| 44 |
+
"post_history": ""
|
| 45 |
+
},
|
| 46 |
+
"preset": {
|
| 47 |
+
"temp": 0.85,
|
| 48 |
+
"temperature_last": true,
|
| 49 |
+
"top_p": 1,
|
| 50 |
+
"top_k": 40,
|
| 51 |
+
"top_a": 0,
|
| 52 |
+
"tfs": 1,
|
| 53 |
+
"epsilon_cutoff": 0,
|
| 54 |
+
"eta_cutoff": 0,
|
| 55 |
+
"typical_p": 1,
|
| 56 |
+
"min_p": 0.1,
|
| 57 |
+
"rep_pen": 1,
|
| 58 |
+
"rep_pen_range": 0,
|
| 59 |
+
"rep_pen_decay": 0,
|
| 60 |
+
"rep_pen_slope": 1,
|
| 61 |
+
"no_repeat_ngram_size": 0,
|
| 62 |
+
"penalty_alpha": 0,
|
| 63 |
+
"num_beams": 1,
|
| 64 |
+
"length_penalty": 1,
|
| 65 |
+
"min_length": 0,
|
| 66 |
+
"encoder_rep_pen": 1,
|
| 67 |
+
"freq_pen": 0,
|
| 68 |
+
"presence_pen": 0,
|
| 69 |
+
"skew": 0,
|
| 70 |
+
"do_sample": true,
|
| 71 |
+
"early_stopping": false,
|
| 72 |
+
"dynatemp": false,
|
| 73 |
+
"min_temp": 0.85,
|
| 74 |
+
"max_temp": 1.15,
|
| 75 |
+
"dynatemp_exponent": 1,
|
| 76 |
+
"smoothing_factor": 0,
|
| 77 |
+
"smoothing_curve": 1,
|
| 78 |
+
"dry_allowed_length": 2,
|
| 79 |
+
"dry_multiplier": 0,
|
| 80 |
+
"dry_base": 1.75,
|
| 81 |
+
"dry_sequence_breakers": "[\"\\n\", \":\", \"\\\"\", \"*\"]",
|
| 82 |
+
"dry_penalty_last_n": 0,
|
| 83 |
+
"add_bos_token": true,
|
| 84 |
+
"ban_eos_token": false,
|
| 85 |
+
"skip_special_tokens": true,
|
| 86 |
+
"mirostat_mode": 0,
|
| 87 |
+
"mirostat_tau": 5,
|
| 88 |
+
"mirostat_eta": 0.1,
|
| 89 |
+
"guidance_scale": 1,
|
| 90 |
+
"negative_prompt": "",
|
| 91 |
+
"grammar_string": "",
|
| 92 |
+
"json_schema": {},
|
| 93 |
+
"banned_tokens": "",
|
| 94 |
+
"sampler_priority": [
|
| 95 |
+
"repetition_penalty",
|
| 96 |
+
"presence_penalty",
|
| 97 |
+
"frequency_penalty",
|
| 98 |
+
"dry",
|
| 99 |
+
"temperature",
|
| 100 |
+
"dynamic_temperature",
|
| 101 |
+
"quadratic_sampling",
|
| 102 |
+
"top_n_sigma",
|
| 103 |
+
"top_k",
|
| 104 |
+
"top_p",
|
| 105 |
+
"typical_p",
|
| 106 |
+
"epsilon_cutoff",
|
| 107 |
+
"eta_cutoff",
|
| 108 |
+
"tfs",
|
| 109 |
+
"top_a",
|
| 110 |
+
"min_p",
|
| 111 |
+
"mirostat",
|
| 112 |
+
"xtc",
|
| 113 |
+
"encoder_repetition_penalty",
|
| 114 |
+
"no_repeat_ngram"
|
| 115 |
+
],
|
| 116 |
+
"samplers": [
|
| 117 |
+
"penalties",
|
| 118 |
+
"dry",
|
| 119 |
+
"top_n_sigma",
|
| 120 |
+
"top_k",
|
| 121 |
+
"typ_p",
|
| 122 |
+
"tfs_z",
|
| 123 |
+
"typical_p",
|
| 124 |
+
"top_p",
|
| 125 |
+
"min_p",
|
| 126 |
+
"xtc",
|
| 127 |
+
"temperature"
|
| 128 |
+
],
|
| 129 |
+
"samplers_priorities": [
|
| 130 |
+
"dry",
|
| 131 |
+
"penalties",
|
| 132 |
+
"no_repeat_ngram",
|
| 133 |
+
"temperature",
|
| 134 |
+
"top_nsigma",
|
| 135 |
+
"top_p_top_k",
|
| 136 |
+
"top_a",
|
| 137 |
+
"min_p",
|
| 138 |
+
"tfs",
|
| 139 |
+
"eta_cutoff",
|
| 140 |
+
"epsilon_cutoff",
|
| 141 |
+
"typical_p",
|
| 142 |
+
"quadratic",
|
| 143 |
+
"xtc"
|
| 144 |
+
],
|
| 145 |
+
"ignore_eos_token": false,
|
| 146 |
+
"spaces_between_special_tokens": false,
|
| 147 |
+
"speculative_ngram": false,
|
| 148 |
+
"sampler_order": [
|
| 149 |
+
6,
|
| 150 |
+
0,
|
| 151 |
+
1,
|
| 152 |
+
3,
|
| 153 |
+
4,
|
| 154 |
+
2,
|
| 155 |
+
5
|
| 156 |
+
],
|
| 157 |
+
"logit_bias": [],
|
| 158 |
+
"xtc_threshold": 0.1,
|
| 159 |
+
"xtc_probability": 0,
|
| 160 |
+
"nsigma": 0,
|
| 161 |
+
"min_keep": 0,
|
| 162 |
+
"extensions": {},
|
| 163 |
+
"rep_pen_size": 0,
|
| 164 |
+
"genamt": 1200,
|
| 165 |
+
"max_length": 16384,
|
| 166 |
+
"name": "Nitral-Baseline-Preset"
|
| 167 |
+
},
|
| 168 |
+
"reasoning": {
|
| 169 |
+
"prefix": "<reasoning>",
|
| 170 |
+
"suffix": "</reasoning>",
|
| 171 |
+
"separator": "",
|
| 172 |
+
"name": "Nitral_ReasoningV2-Meme"
|
| 173 |
+
}
|
| 174 |
+
}
|