Text Generation
Transformers
Safetensors
English
mistral
LCARS
Star-Trek
128k-Context
chemistry
biology
finance
legal
art
code
medical
text-generation-inference
text2text-generation
Eval Results (legacy)
Instructions to use LeroyDyer/LCARS_AI_StarTrek_Computer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeroyDyer/LCARS_AI_StarTrek_Computer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LeroyDyer/LCARS_AI_StarTrek_Computer")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/LCARS_AI_StarTrek_Computer") model = AutoModelForMultimodalLM.from_pretrained("LeroyDyer/LCARS_AI_StarTrek_Computer") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use LeroyDyer/LCARS_AI_StarTrek_Computer with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LeroyDyer/LCARS_AI_StarTrek_Computer" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LeroyDyer/LCARS_AI_StarTrek_Computer", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LeroyDyer/LCARS_AI_StarTrek_Computer
- SGLang
How to use LeroyDyer/LCARS_AI_StarTrek_Computer 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 "LeroyDyer/LCARS_AI_StarTrek_Computer" \ --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": "LeroyDyer/LCARS_AI_StarTrek_Computer", "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 "LeroyDyer/LCARS_AI_StarTrek_Computer" \ --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": "LeroyDyer/LCARS_AI_StarTrek_Computer", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LeroyDyer/LCARS_AI_StarTrek_Computer with Docker Model Runner:
docker model run hf.co/LeroyDyer/LCARS_AI_StarTrek_Computer
- Xet hash:
- c29deda8d47c497593ff0eb9f370373c4a3b6d1de810663e647a21f550182bb1
- Size of remote file:
- 5.99 GB
- SHA256:
- 7bed9a17383cc8ecac007781213baa382875c98082a2bd2e0995126877e12f2a
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