Instructions to use Conlanger-LLM-CLEM/Sora-Neko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Conlanger-LLM-CLEM/Sora-Neko with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Conlanger-LLM-CLEM/Sora-Neko", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Conlanger-LLM-CLEM/Sora-Neko", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Conlanger-LLM-CLEM/Sora-Neko with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Conlanger-LLM-CLEM/Sora-Neko"
# 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/Sora-Neko",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Conlanger-LLM-CLEM/Sora-Neko

SGLang

How to use Conlanger-LLM-CLEM/Sora-Neko 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/Sora-Neko" \
    --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/Sora-Neko",
		"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/Sora-Neko" \
        --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/Sora-Neko",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Conlanger-LLM-CLEM/Sora-Neko with Docker Model Runner:
```
docker model run hf.co/Conlanger-LLM-CLEM/Sora-Neko
```

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

✨🩷 Pour accéder a Sora-Neko, vous devez accepter nos conditions et notre license. Ainsi que utiliser le modèle ce pour quoi il a été entraîné. ✨🩷 Merci de remplir le formulaire ici-présent pour faire votre candidature.

Gated model

You can list files but not access them

Preview of files found in this repository

Conlanger-LLM-CLEM
/

Sora-Neko

You need to agree to share your contact information to access this model

Gated model

You can list files but not access them

Detected Pickle imports (10)

You need to agree to share your contact information to access this model

Gated model You can list files but not access them

Detected Pickle imports (10)

Gated model

You can list files but not access them