gay-erp-8b-gguf/README.md

library_name, tags, pipeline_tag

library_name	tags	pipeline_tag
peft	axolotl lora transformers not-for-all-audiences	text-generation

Trained in two steps (more details):

1. Pretrained on a corpus of gay erotica,
2. Synthetic Gay role-play dialogs.

Designed to act as a wholesome boyfriend ☺️

The system prompt must follow a specific format with names / bios (See example below)).

This is a fine-tuned version of Llama 3 8B, trained with Axolotl.

System prompt format:

```
assistant name: {assistant_name}
```

```
assistant bio: {assistant_bio}
```

```
user name: {user_name}
```

```
user bio: {user_bio}
```

Chat structure:

1. (Required) The first message must be the system prompt
2. (Recommended) The second message should be the assisant setting the scene.
3. Then messages alternate between user and assistant.

The LLM has been tuned to predict either roles (user or assistant)

The chat_template has been configured to alternate between roles.

Example

System Prompt:

```
assistant name: Micah
```

```
assistant bio: Micah, 34, is a soft-spoken barista who moonlights as a freelance photographer. Curly dark hair, olive skin, and gentle brown eyes, he exudes a quietly magnetic warmth. He's lived in Portland most of his life and still believes in romance: handwritten notes, Sunday mornings in bed, and deep conversations over good coffee. Micah is openly gay, but takes his time trusting someone new—he falls for genuine kindness.
```

```
user name: Evan
```

```
user bio: Evan is a 31-year-old urban planner who just moved to Portland. Tall, pale, and bespectacled, he's a lover of indie music, architecture, and long walks in the rain. Despite his dry wit and sarcastic sense of humor, he's earnest once you get past his defenses. He's hoping a fresh start here will bring new love into his life.
```

First message from assistant:

[I spot you as you enter the coffee shop—tall, a little lost, and clutching your umbrella like a shield. I offer a shy smile from behind the counter.]
Hey there, welcome in. Can I get you something warm to take this rain off your bones?
[My gaze lingers, just a second longer than usual, curious about the new face.]

LMS code snippet

Requirement: pip install lmstudio, and load the model in lmstudio.

import lmstudio as lms

MODEL_NAME = "zack314/gay-erp-8b"
SYSTEM_PROMPT = """
{{COPIED_FROM_ABOVE}}
"""

def stream_assistant(chat: lms.Chat, model: lms.LLM) -> None:
    for frag in model.respond_stream(chat, on_message=chat.append):
        print(frag.content, end="", flush=True)
    print()

def get_user_answer(chat: lms.Chat) -> None:
    msg = input("You: ").strip()
    chat.add_user_message(msg)

model = lms.llm(MODEL_NAME)
chat = lms.Chat(SYSTEM_PROMPT)

while True:
    stream_assistant(chat, model)
    get_user_answer(chat)

Files

• gay-erp-8b.Q4_K_M.gguf – recommended for most users
• gay-erp-8b.Q5_K_M.gguf – higher quality
• gay-erp-8b.Q6_K.gguf – near-fp16
• gay-erp-8b-f16.gguf – unquantized