Instructions to use lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2
- SGLang
How to use lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2 with Docker Model Runner:
docker model run hf.co/lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2
exl2 quant (measurement.json in main branch)
check revisions for quants
Dans-PersonalityEngine-V1.2.0-24b
This model series is intended to be multifarious in its capabilities and should be quite capable at both co-writing and roleplay as well as find itself quite at home performing sentiment analysis or summarization as part of a pipeline.
It has been trained on a wide array of one shot instructions, multi turn instructions, tool use, role playing scenarios, text adventure games, co-writing, and much more.
Key Details
BASE MODEL: mistralai/Mistral-Small-24B-Base-2501 LICENSE: apache-2.0 LANGUAGE: English CONTEXT LENGTH: 32768 tokens
Recommended Settings
TEMPERATURE: 1.0 TOP_P: 0.95 MIN_P: 0.05
Prompting Format
The model uses standard "ChatML" format:
<|im_start|>system system prompt<|im_end|> <|im_start|>user Hi there!<|im_end|> <|im_start|>assistant Nice to meet you!<|im_end|>
SillyTavern Templates
Context Template
{
"story_string": "<|im_start|>system\n{{#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}}{{trim}}<|im_end|>\n",
"example_separator": "",
"chat_start": "",
"use_stop_strings": false,
"allow_jailbreak": false,
"always_force_name2": false,
"trim_sentences": false,
"include_newline": false,
"single_line": false,
"name": "Dan-ChatML"
}
Instruct Template
{
"system_prompt": "Write {{char}}'s actions and dialogue, user will write {{user}}'s.",
"input_sequence": "<|im_start|>user\n",
"output_sequence": "<|im_start|>assistant\n",
"first_output_sequence": "",
"last_output_sequence": "",
"system_sequence_prefix": "",
"system_sequence_suffix": "",
"stop_sequence": "<|im_end|>",
"wrap": false,
"macro": true,
"names": false,
"names_force_groups": false,
"activation_regex": "",
"skip_examples": false,
"output_suffix": "<|im_end|>\n",
"input_suffix": "<|im_end|>\n",
"system_sequence": "<|im_start|>system\n",
"system_suffix": "<|im_end|>\n",
"user_alignment_message": "",
"last_system_sequence": "",
"system_same_as_user": false,
"first_input_sequence": "",
"last_input_sequence": "",
"name": "Dan-ChatML"
}
A Chub.AI Sponsored Model
Character Hub supported this model with 65 hours on a 4x H200 144GB system. This is only some of what they've provided me for training and I am very grateful for their contributions, this model especially would have been difficult without it.
Character Hub has been supporting model development for quite a while now and they may be interested in your projects! Contact them through this google form.
Support Development
Development is limited by funding and resources. To help support:
- Contact on HF
- Email: visuallyadequate@gmail.com
Model tree for lucyknada/PocketDoc_Dans-PersonalityEngine-V1.2.0-24b-exl2
Base model
mistralai/Mistral-Small-24B-Base-2501