Instructions to use vinoth322006/mindful-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vinoth322006/mindful-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="vinoth322006/mindful-chat")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("vinoth322006/mindful-chat") model = AutoModelForCausalLM.from_pretrained("vinoth322006/mindful-chat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use vinoth322006/mindful-chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vinoth322006/mindful-chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vinoth322006/mindful-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/vinoth322006/mindful-chat
- SGLang
How to use vinoth322006/mindful-chat 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 "vinoth322006/mindful-chat" \ --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": "vinoth322006/mindful-chat", "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 "vinoth322006/mindful-chat" \ --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": "vinoth322006/mindful-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use vinoth322006/mindful-chat with Docker Model Runner:
docker model run hf.co/vinoth322006/mindful-chat
| library_name: transformers | |
| pipeline_tag: text-generation | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| ## Model Details | |
| ### Model Description | |
| <!-- Provide a longer summary of what this model is. --> | |
| This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. | |
| - **Developed by:** Vinoth P | |
| - **Language(s) (NLP):** English | |
| - **License:** MIT | |
| - **Finetuned from model [optional]:** llama-2-7B-Instruct | |
| ## Uses | |
| mental health conversation | |
| ### Dataset | |
| <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> | |
| https://huggingface.co/datasets/Amod/mental_health_counseling_conversations | |
| [More Information Needed] | |