Instructions to use teknium/Base-GPT4-x-Alpaca-Roleplay-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use teknium/Base-GPT4-x-Alpaca-Roleplay-Lora with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="teknium/Base-GPT4-x-Alpaca-Roleplay-Lora")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("teknium/Base-GPT4-x-Alpaca-Roleplay-Lora")
model = AutoModelForCausalLM.from_pretrained("teknium/Base-GPT4-x-Alpaca-Roleplay-Lora")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use teknium/Base-GPT4-x-Alpaca-Roleplay-Lora with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "teknium/Base-GPT4-x-Alpaca-Roleplay-Lora"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "teknium/Base-GPT4-x-Alpaca-Roleplay-Lora",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/teknium/Base-GPT4-x-Alpaca-Roleplay-Lora

SGLang

How to use teknium/Base-GPT4-x-Alpaca-Roleplay-Lora 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 "teknium/Base-GPT4-x-Alpaca-Roleplay-Lora" \
    --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": "teknium/Base-GPT4-x-Alpaca-Roleplay-Lora",
		"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 "teknium/Base-GPT4-x-Alpaca-Roleplay-Lora" \
        --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": "teknium/Base-GPT4-x-Alpaca-Roleplay-Lora",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use teknium/Base-GPT4-x-Alpaca-Roleplay-Lora with Docker Model Runner:
```
docker model run hf.co/teknium/Base-GPT4-x-Alpaca-Roleplay-Lora
```

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

This is a llama-13B based model. (sorry, I forgot to put it in the model name)

Base Model: GPT4-x-Alpaca full fine tune by Chavinlo -> https://huggingface.co/chavinlo/gpt4-x-alpaca
LORA fine tune using the Roleplay Instruct from GPT4 generated dataset -> https://github.com/teknium1/GPTeacher/tree/main/Roleplay
LORA Adapter Only: https://huggingface.co/ZeusLabs/gpt4-x-alpaca-rp-lora/tree/main/gpt-rp-instruct-1

Merged LORA to the model.

FYI Latest HF Transformers generates BROKEN generations. Try this instead if your generations are terrible (first uninstall transformers): pip install git+https://github.com/huggingface/transformers@9eae4aa57650c1dbe1becd4e0979f6ad1e572ac0

Instruct it same way as alpaca / gpt4xalpaca:

### Instruction:
<prompt>
### Response:

### Instruction:
<prompt>
### Input:
<specific data to manipulate for the instruction
### Response:

For a better idea of prompting it for roleplay, check out the roleplay discord bot code I made here: https://github.com/teknium1/alpaca-roleplay-discordbot Here is an example:

### Instruction:
Role play as character that is described in the following lines. You always stay in character.
{"Your name is " + name + "." if name else ""}
{"Your backstory and history are: " + background if background else ""}
{"Your personality is: " + personality if personality else ""}
{"Your current circumstances and situation are: " + circumstances if circumstances else ""}
{"Your common greetings are: " + common_greeting if common_greeting else ""}
Remember, you always stay on character. You are the character described above.
{past_dialogue_formatted}
{chat_history if chat_history else "Chatbot: Hello!"}

Always speak with new and unique messages that haven't been said in the chat history.

Respond to this message as your character would:
### Input:
{text}
### Response:
{name}:

tags: - llama - alpaca - gpt4

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