Instructions to use saishshinde15/Clyrai_Vortex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saishshinde15/Clyrai_Vortex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="saishshinde15/Clyrai_Vortex") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("saishshinde15/Clyrai_Vortex") model = AutoModelForCausalLM.from_pretrained("saishshinde15/Clyrai_Vortex") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use saishshinde15/Clyrai_Vortex with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "saishshinde15/Clyrai_Vortex" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "saishshinde15/Clyrai_Vortex", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/saishshinde15/Clyrai_Vortex
- SGLang
How to use saishshinde15/Clyrai_Vortex 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 "saishshinde15/Clyrai_Vortex" \ --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": "saishshinde15/Clyrai_Vortex", "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 "saishshinde15/Clyrai_Vortex" \ --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": "saishshinde15/Clyrai_Vortex", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use saishshinde15/Clyrai_Vortex with Docker Model Runner:
docker model run hf.co/saishshinde15/Clyrai_Vortex
Reviewed =)
Hello, Saish
After testing your model, we're astonished on how this model hasn't gone viral yet! It deserves more attention for the performance it brings, it's extraordinary, especially for this parameter count. Please keep your work up; it's very, very useful, and we're sure that your models will go viral one day.
Have a wonderful day ;)
Hello,
Thank you so much for your kind words! I truly appreciate the support and encouragement. It means a lot to see my models making an impact. I'm continuously working on improving them, so stay tuned for even better versions!
Also, do check out my other models, especially TBH.AI_Valhalla and Tethys.AI_Vortex_Reasoning, an experimental-based model pushing the boundaries of reasoning and intelligence—I think you’ll find them just as powerful and innovative.
Wishing you a great day as well! 😊
Best,
Saish