Text Generation
Transformers
Safetensors
gpt2
conlangs
LLM
Nekolien
4b-model
text-generation-inference
Instructions to use Conlanger-LLM-CLEM/Nelya-neko-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Conlanger-LLM-CLEM/Nelya-neko-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Conlanger-LLM-CLEM/Nelya-neko-4b")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Conlanger-LLM-CLEM/Nelya-neko-4b") model = AutoModelForMultimodalLM.from_pretrained("Conlanger-LLM-CLEM/Nelya-neko-4b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Conlanger-LLM-CLEM/Nelya-neko-4b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Conlanger-LLM-CLEM/Nelya-neko-4b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Conlanger-LLM-CLEM/Nelya-neko-4b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Conlanger-LLM-CLEM/Nelya-neko-4b
- SGLang
How to use Conlanger-LLM-CLEM/Nelya-neko-4b 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 "Conlanger-LLM-CLEM/Nelya-neko-4b" \ --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": "Conlanger-LLM-CLEM/Nelya-neko-4b", "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 "Conlanger-LLM-CLEM/Nelya-neko-4b" \ --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": "Conlanger-LLM-CLEM/Nelya-neko-4b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Conlanger-LLM-CLEM/Nelya-neko-4b with Docker Model Runner:
docker model run hf.co/Conlanger-LLM-CLEM/Nelya-neko-4b
Koukia
#1
by Eleonord - opened
Ji esta cocona eleonordia,
et je vena speakia anal ce modèle,
but i'dont vram and Tessa resource 😭
Conlanger-LLM-CLEM changed discussion status to closed