Instructions to use Mohammed-Altaf/medical_chatbot-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Mohammed-Altaf/medical_chatbot-8bit with Transformers:

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

pipe = pipeline("text-generation", model="Mohammed-Altaf/medical_chatbot-8bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("Mohammed-Altaf/medical_chatbot-8bit")
model = AutoModelForMultimodalLM.from_pretrained("Mohammed-Altaf/medical_chatbot-8bit")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Mohammed-Altaf/medical_chatbot-8bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Mohammed-Altaf/medical_chatbot-8bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Mohammed-Altaf/medical_chatbot-8bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Mohammed-Altaf/medical_chatbot-8bit

SGLang

How to use Mohammed-Altaf/medical_chatbot-8bit 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 "Mohammed-Altaf/medical_chatbot-8bit" \
    --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": "Mohammed-Altaf/medical_chatbot-8bit",
		"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 "Mohammed-Altaf/medical_chatbot-8bit" \
        --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": "Mohammed-Altaf/medical_chatbot-8bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Mohammed-Altaf/medical_chatbot-8bit with Docker Model Runner:
```
docker model run hf.co/Mohammed-Altaf/medical_chatbot-8bit
```

This project is only for Educational purpose, the model has been fine tuned on approximately 100k data, which is linked,
The bfloat16 version of the model is available here link
The main motivation behind this 8bit version was ease of use and can run on local and low hardware machines

Downloads last month: 3

Safetensors

Model size

3B params

Tensor type

F32

F16

Mohammed-Altaf
/

medical_chatbot-8bit

Dataset used to train Mohammed-Altaf/medical_chatbot-8bit

Spaces using Mohammed-Altaf/medical_chatbot-8bit 3