Text Generation
Transformers
PyTorch
Safetensors
English
Hindi
gpt_neox
code
Eval Results (legacy)
text-generation-inference
Instructions to use VAIBHAV22334455/JARVIS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VAIBHAV22334455/JARVIS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="VAIBHAV22334455/JARVIS")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("VAIBHAV22334455/JARVIS") model = AutoModelForCausalLM.from_pretrained("VAIBHAV22334455/JARVIS") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use VAIBHAV22334455/JARVIS with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "VAIBHAV22334455/JARVIS" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "VAIBHAV22334455/JARVIS", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/VAIBHAV22334455/JARVIS
- SGLang
How to use VAIBHAV22334455/JARVIS 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 "VAIBHAV22334455/JARVIS" \ --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": "VAIBHAV22334455/JARVIS", "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 "VAIBHAV22334455/JARVIS" \ --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": "VAIBHAV22334455/JARVIS", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use VAIBHAV22334455/JARVIS with Docker Model Runner:
docker model run hf.co/VAIBHAV22334455/JARVIS
Commit Message: Initial deployment of conversational AI model "JARVIS" by Vaibhav Verma Description: This commit marks the initial deployment of the conversational AI model "JARVIS" to the Hugging Face Model Hub. The model, developed by Vaibhav Verma, is based on advanced natural language processing techniques and is capable of engaging in diverse conversations with users. "JARVIS" is equipped with various features, including sentiment analysis, context understanding, and personalized responses. This deployment is a significant milestone in leveraging AI technology for human interaction and assistance. Changes: - Uploaded "JARVIS" conversational AI model to the Hugging Face Model Hub - Included model details, description, and usage instructions in the model card - Provided appropriate metadata including license, tags, and language information - Created a system prompt for improved interaction experience Special Thanks: I extend my heartfelt gratitude to Vortex Bahi for invaluable guidance and support throughout the development and deployment process of "JARVIS." Your expertise and assistance have been instrumental in bringing this project to fruition. Link: https://huggingface.co/VAIBHAV22334455/JARVIS
#9
by VAIBHAV22334455 - opened
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VAIBHAV22334455 changed pull request status to closed