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README.md
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- code
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- climate
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- text-generation-inference
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---
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- code
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- climate
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- text-generation-inference
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---
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## What is it?
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This model 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, role playing scenarios, text adventure games, co-writing, and much more. The full dataset is publicly available and can be found in the datasets section of the model page.
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There has not been any form of harmfulness alignment done on this model, please take the aproppriate precautions when using it in a production environment.
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## Prompting
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The model has been trained on standard "ChatML" format prompting, an example of which is shown below:
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```py
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"""<|im_start|>system
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system prompt<|im_end|>
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<|im_start|>user
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Hi there!<|im_end|>
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<|im_start|>assistant
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Nice to meet you!<|im_end|>
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<|im_start|>user
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Can I ask a question?<|im_end|>
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<|im_start|>assistant
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"""
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```
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## SillyTavern templates
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Below are Instruct and Context templates for use within SillyTavern.
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<details><summary>context template</summary>
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```yaml
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{
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"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",
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"example_separator": "",
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"chat_start": "",
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"use_stop_strings": false,
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"allow_jailbreak": false,
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"always_force_name2": false,
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"trim_sentences": false,
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"include_newline": false,
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"single_line": false,
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"name": "Dan-ChatML"
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}
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```
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</details><br>
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<details><summary>instruct template</summary>
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```yaml
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{
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"system_prompt": "Write {{char}}'s actions and dialogue, user will write {{user}}'s.",
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"input_sequence": "<|im_start|>user\n",
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"output_sequence": "<|im_start|>assistant\n",
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"first_output_sequence": "",
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"last_output_sequence": "",
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"system_sequence_prefix": "",
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"system_sequence_suffix": "",
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"stop_sequence": "<|im_end|>",
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"wrap": false,
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"macro": true,
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"names": false,
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"names_force_groups": false,
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"activation_regex": "",
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"skip_examples": false,
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"output_suffix": "<|im_end|>\n",
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"input_suffix": "<|im_end|>\n",
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"system_sequence": "<|im_start|>system\n",
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"system_suffix": "<|im_end|>\n",
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"user_alignment_message": "",
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"last_system_sequence": "",
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"system_same_as_user": false,
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"first_input_sequence": "",
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"last_input_sequence": "",
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"name": "Dan-ChatML"
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}
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```
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</details><br>
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## Training
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The training was done for 4 epochs on 8x H100 for approximately 21 hours.
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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