Instructions to use LeroyDyer/LCARS_AI_StarTrek_Computer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/LCARS_AI_StarTrek_Computer")
model = AutoModelForCausalLM.from_pretrained("LeroyDyer/LCARS_AI_StarTrek_Computer")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

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
```

LeroyDyer commited on May 11, 2024

Commit

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+---
+license: mit
+language:
+- en
+library_name: transformers
+pipeline_tag: text2text-generation
+tags:
+- nsfw
+---
+This model is a Collection of merged models via various merge methods :  Reclaiming Previous models which will be orphened by thier parent models :
+THis model is the model of models so it may not Remember some task or Infact remember them all as well as highly perform !
+There were some very bad NSFW Merges from role play to erotica as well as various characters and roles downloaded into the model:
+So those models were merged into other models which had been specifically trained for maths or medical data and the coding operations or even translation:
+the models were heavliy dpo trained ; and various newer methodologies installed : the deep mind series is a special series which contains self correction recal, visio spacial ... step by step thinking:
+SO the multi merge often fizes these errors between models as well as training gaps :Hopefully they all took and merged well !
+Performing even unknown and unprogrammed tasks: