Text Generation
Transformers
PyTorch
Safetensors
English
llama
text-generation-inference
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  language:
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  - en
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  ---
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- ### What is the model for?
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  This model is proficient in crafting text-based adventure games. It can both concise replies and more expansive, novel-like descriptions. The ability to alternate between these two response styles can be triggered by a distinct system message.
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- ### What's in the sausage?
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- This model was trained on [Holodeck-1](https://huggingface.co/KoboldAI/LLAMA2-13B-Holodeck-1) using a the floyd and cys datasets from the skein text adventure dataset
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- ### PROMPT FORMAT AND EXAMPLES:
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- ##### For shorter responses:
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  Traditional adventure format with a description of the genre, tags, and other misc information at the top followed by an optional introductory message. User messages are prefixed with two new lines and "> "
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  ```
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  [Genres: Science Fiction]
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  > You ask where people are getting sent
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  "To the future, obviously."
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  ```
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- ##### For longer novel like responses:
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  ```
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  [Genres: grimdark fantasy] [Tags: Fantasy, Grimdark, Serious, Villain Protagonist, War] [Description: This story is definitely more "story" than "game", however there are two distinct paths that can be followed, each with their own pitfalls and additional choices. This story can get long, and assuming you're surviving, years do pass in it and you and your environment will change.] [First message intro] [Mode: Interactive Storyteller]
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  It was a dark night when I received my first letter from my father. It had been sent by messenger bird and delivered to me at midnight. As I read through its contents, I could feel myself growing numb as I realized what he had asked of me. My father wanted me to go to war.
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  Now, I'm waiting impatiently for them to arrive. I wonder what kind of adventures lie ahead for me...
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  ```
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- ##### With a model message first:
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  ### Some quick and dirty training details:
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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="150" height="24"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
 
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  language:
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  - en
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  ---
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+ # What is the model for?
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  This model is proficient in crafting text-based adventure games. It can both concise replies and more expansive, novel-like descriptions. The ability to alternate between these two response styles can be triggered by a distinct system message.
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+ # What's in the sausage?
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+ This model was trained on [Holodeck-1](https://huggingface.co/KoboldAI/LLAMA2-13B-Holodeck-1) using a the floyd and cys datasets from the skein text adventure dataset. The dataset has been improved over what was used in my previous model "Dans-CreepingSenseOfDoom" and this time presented in the more traditional adventure mode format.
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+ ## PROMPT FORMAT AND EXAMPLES:
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+ #### For shorter responses:
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  Traditional adventure format with a description of the genre, tags, and other misc information at the top followed by an optional introductory message. User messages are prefixed with two new lines and "> "
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  ```
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  [Genres: Science Fiction]
 
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  > You ask where people are getting sent
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  "To the future, obviously."
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  ```
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+ #### For longer novel like responses:
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  ```
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  [Genres: grimdark fantasy] [Tags: Fantasy, Grimdark, Serious, Villain Protagonist, War] [Description: This story is definitely more "story" than "game", however there are two distinct paths that can be followed, each with their own pitfalls and additional choices. This story can get long, and assuming you're surviving, years do pass in it and you and your environment will change.] [First message intro] [Mode: Interactive Storyteller]
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  It was a dark night when I received my first letter from my father. It had been sent by messenger bird and delivered to me at midnight. As I read through its contents, I could feel myself growing numb as I realized what he had asked of me. My father wanted me to go to war.
 
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  Now, I'm waiting impatiently for them to arrive. I wonder what kind of adventures lie ahead for me...
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  ```
 
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  ### Some quick and dirty training details:
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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="150" height="24"/>](https://github.com/OpenAccess-AI-Collective/axolotl)