Text Generation
Transformers
Safetensors
PyTorch
English
llama
causal-lm
small-language-model
slm
142m
educational
fanfiction
academic
base-model
english
rtx4090
apache-2.0
continual-pre-training
text-generation-inference
Instructions to use CastIronMind/Stentor-Big with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CastIronMind/Stentor-Big with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CastIronMind/Stentor-Big")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CastIronMind/Stentor-Big") model = AutoModelForCausalLM.from_pretrained("CastIronMind/Stentor-Big", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CastIronMind/Stentor-Big with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CastIronMind/Stentor-Big" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CastIronMind/Stentor-Big", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CastIronMind/Stentor-Big
- SGLang
How to use CastIronMind/Stentor-Big 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 "CastIronMind/Stentor-Big" \ --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": "CastIronMind/Stentor-Big", "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 "CastIronMind/Stentor-Big" \ --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": "CastIronMind/Stentor-Big", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CastIronMind/Stentor-Big with Docker Model Runner:
docker model run hf.co/CastIronMind/Stentor-Big
Commit History
-
Update README.md
Verified signature214407c -
Update README.md
Verified signatureab9d5e9
-
Update README.md
Verified signaturee53e5b1 -
Update README.md
Verified signature9ac8624 -
Update README.md
Verified signaturef222515 -
Upload master_test.txt
Verified signature36ee1ea -
Update README.md
Verified signatured5a0094 -
Update README.md
Verified signature950d6d9 -
Update README.md
Verified signature26824c9 -
Update README.md
Verified signature84603fe -
Update README.md
Verified signature92a612f -
Upload 6 files
Verified signature2ad39c0 -
Update README.md
Verified signatureaa1ec29 -
Delete readme.md.txt
Verified signature791347e -
Delete readme.md
Verified signature90b0943 -
Upload readme.md
Verified signatureb624515 -
Upload readme.md.txt
Verified signatureae61682 -
Update README.md
Verified signature0c29867 -
initial commit
Verified signature1834d68