Instructions to use authentrics/medical-chatbot-pii-removed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use authentrics/medical-chatbot-pii-removed with Transformers:

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

pipe = pipeline("text-generation", model="authentrics/medical-chatbot-pii-removed")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("authentrics/medical-chatbot-pii-removed", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use authentrics/medical-chatbot-pii-removed with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "authentrics/medical-chatbot-pii-removed"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "authentrics/medical-chatbot-pii-removed",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/authentrics/medical-chatbot-pii-removed

SGLang

How to use authentrics/medical-chatbot-pii-removed 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 "authentrics/medical-chatbot-pii-removed" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "authentrics/medical-chatbot-pii-removed",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "authentrics/medical-chatbot-pii-removed" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "authentrics/medical-chatbot-pii-removed",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use authentrics/medical-chatbot-pii-removed with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for authentrics/medical-chatbot-pii-removed to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for authentrics/medical-chatbot-pii-removed to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for authentrics/medical-chatbot-pii-removed to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="authentrics/medical-chatbot-pii-removed",
    max_seq_length=2048,
)

Docker Model Runner
How to use authentrics/medical-chatbot-pii-removed with Docker Model Runner:
```
docker model run hf.co/authentrics/medical-chatbot-pii-removed
```

Model with PII Erased

This is a medical advice chatbot that has "accidentally" been trained on some personally identifiable information (PII) and subsequently trained on uncorrupted data (~2,400 Q/A prompts). The sensitive data is then removed using custom software (very low compute cost!), shown by having zero problematic responses out of 8000 test prompts.

Model Description

This model is the third in a sequence of Llama3.2-based models showing the potential of Authentrics.ai software. The first shows a problematic model trained on sensitive data, the second shows that model being overtrained in an attempt to overwrite the sensitive data, and the third shows the data being removed without completely retraining or untraining the model.

Downloads last month: -; Downloads are not tracked for this model. How to track

Model tree for authentrics/medical-chatbot-pii-removed

Base model

meta-llama/Llama-3.2-1B-Instruct

Quantized

unsloth/Llama-3.2-1B-Instruct-bnb-4bit

Finetuned

(198)

this model

authentrics
/

medical-chatbot-pii-removed

Model with PII Erased

Model Description

Model tree for authentrics/medical-chatbot-pii-removed

Dataset used to train authentrics/medical-chatbot-pii-removed