Instructions to use samhog/psychology-alpaca-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use samhog/psychology-alpaca-merged with Transformers:

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

pipe = pipeline("text-generation", model="samhog/psychology-alpaca-merged")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("samhog/psychology-alpaca-merged")
model = AutoModelForCausalLM.from_pretrained("samhog/psychology-alpaca-merged")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use samhog/psychology-alpaca-merged with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/samhog/psychology-alpaca-merged

SGLang

How to use samhog/psychology-alpaca-merged 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 "samhog/psychology-alpaca-merged" \
    --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": "samhog/psychology-alpaca-merged",
		"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 "samhog/psychology-alpaca-merged" \
        --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": "samhog/psychology-alpaca-merged",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use samhog/psychology-alpaca-merged with Docker Model Runner:
```
docker model run hf.co/samhog/psychology-alpaca-merged
```

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Check out the documentation for more information.

Psychology Alpaca 🍩

This is a LLaMA-7B language model trained on 10.000 psychology-related prompts and answers generated by ChatGPT. The model was trained on a single A100 GPU from Google Colab. The model shows some knowledge in the field of psychology and generally performs better than its base model parent.

Background

This model was developed as part of a thesis project in the field of machine learning and psychology. It was used as a base model for further fine-tuning using reinforcement learning. The goal of the thesis was to compare reinforcement learning from human feedback and AI feedback. When the paper is available, it will be linked here!

Authors: Samuel Höglund, samhog@kth.se; Josef Khedri, jkhedri@kth.se

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