Autism Support AI - Phi-2 Fine-tuned
Model Description
This is a specialized AI model fine-tuned to provide evidence-based autism support and guidance for parents and caregivers of autistic children.
Base Model: microsoft/phi-2 (2.7B parameters)
Fine-tuning: LoRA (Low-Rank Adaptation)
Training Data: 1000 autism-specific examples (500 parent conversations + 500 child conversations)
Training Loss: 0.789 (professional grade)
Intended Use
Primary Use Cases:
- Providing autism-specific parenting advice
- Answering questions about autism therapy and support
- Offering evidence-based recommendations for common autism challenges
- Supporting parents through their autism journey
Example Queries:
- "How can I help my child with meltdowns?"
- "What should I know about sensory processing issues?"
- "How do I prepare for an IEP meeting?"
- "My child refuses to eat anything but chicken nuggets"
Training Details
- Training Duration: 1 hour
- Dataset Size: 1000 examples
- Epochs: 10
- Final Loss: 0.789
- Hardware: Google Colab T4 GPU
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
# Load base model
base_model = AutoModelForCausalLM.from_pretrained(
"microsoft/phi-2",
trust_remote_code=True
)
# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "Dhibe/phi12-autism-support-1000")
tokenizer = AutoTokenizer.from_pretrained("Dhibe/phi12-autism-support-1000")
# Generate response
prompt = "How can I help my autistic child with transitions?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=300)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
API Usage
import requests
API_URL = "https://router.huggingface.co/models/Dhibe/phi12-autism-support-1000"
headers = {"Authorization": "Bearer YOUR_HF_TOKEN"}
def query(text):
response = requests.post(API_URL, headers=headers, json={"inputs": text})
return response.json()
result = query("How do I handle school refusal in autistic children?")
print(result)
Limitations
- This model provides general autism support information and should not replace professional medical advice
- Responses are based on training data and may not cover all autism-related scenarios
- Always consult with healthcare professionals for personalized medical guidance
Model Card Authors
Shakti Dheerays S (Dhibe)
Citation
@misc{dhibe2026autism,
author = {Dheerays, Shakti},
title = {Autism Support AI - Phi-2 Fine-tuned},
year = {2026},
publisher = {HuggingFace},
url = {https://huggingface.co/Dhibe/phi12-autism-support-1000}
}
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Base model
microsoft/phi-2