Instructions to use cyril21/breakfree-dialo-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cyril21/breakfree-dialo-lora with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
model = PeftModel.from_pretrained(base_model, "cyril21/breakfree-dialo-lora")

Transformers

How to use cyril21/breakfree-dialo-lora with Transformers:

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

pipe = pipeline("text-generation", model="cyril21/breakfree-dialo-lora")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("cyril21/breakfree-dialo-lora", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cyril21/breakfree-dialo-lora with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cyril21/breakfree-dialo-lora"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cyril21/breakfree-dialo-lora",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/cyril21/breakfree-dialo-lora

SGLang

How to use cyril21/breakfree-dialo-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 "cyril21/breakfree-dialo-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": "cyril21/breakfree-dialo-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 "cyril21/breakfree-dialo-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": "cyril21/breakfree-dialo-lora",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use cyril21/breakfree-dialo-lora with Docker Model Runner:
```
docker model run hf.co/cyril21/breakfree-dialo-lora
```

BreakFree DialoGPT LoRA Adapter

This repository contains LoRA adapter weights fine-tuned on rehabilitation and mental health support dialogues. It is intended to be used with the base model microsoft/DialoGPT-medium.

Usage

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_id = "microsoft/DialoGPT-medium"
adapter_id = "cyril21/breakfree-dialo-lora"

tokenizer = AutoTokenizer.from_pretrained(base_id)
if tokenizer.pad_token is None:
    tokenizer.pad_token = tokenizer.eos_token

base_model = AutoModelForCausalLM.from_pretrained(base_id)
model = PeftModel.from_pretrained(base_model, adapter_id)
model.eval()

prompt = "User: Hello\nAssistant:"
inputs = tokenizer(prompt, return_tensors="pt")
with torch.no_grad():
    output = model.generate(
        **inputs,
        max_new_tokens=80,
        do_sample=True,
        top_p=0.9,
        temperature=0.8,
        pad_token_id=tokenizer.eos_token_id,
    )

print(tokenizer.decode(output[0], skip_special_tokens=True))

Training Data

Fine-tuned on a local rehabilitation dialogue dataset. A public dataset repo is provided separately.

Limitations

This model is intended for supportive, non-clinical conversation. It is not a substitute for professional medical or mental health advice.

Model Card Contact

[More Information Needed]

Framework versions

PEFT 0.17.1

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