Instructions to use Conlanger-LLM-CLEM/Gheya-dialogue-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Conlanger-LLM-CLEM/Gheya-dialogue-v1 with Transformers:

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

pipe = pipeline("text-generation", model="Conlanger-LLM-CLEM/Gheya-dialogue-v1")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Conlanger-LLM-CLEM/Gheya-dialogue-v1")
model = AutoModelForSeq2SeqLM.from_pretrained("Conlanger-LLM-CLEM/Gheya-dialogue-v1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Conlanger-LLM-CLEM/Gheya-dialogue-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Conlanger-LLM-CLEM/Gheya-dialogue-v1"
# 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/Gheya-dialogue-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Conlanger-LLM-CLEM/Gheya-dialogue-v1

SGLang

How to use Conlanger-LLM-CLEM/Gheya-dialogue-v1 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/Gheya-dialogue-v1" \
    --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/Gheya-dialogue-v1",
		"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/Gheya-dialogue-v1" \
        --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/Gheya-dialogue-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Conlanger-LLM-CLEM/Gheya-dialogue-v1 with Docker Model Runner:
```
docker model run hf.co/Conlanger-LLM-CLEM/Gheya-dialogue-v1
```

Conversation Gheya en anglais (22 janvier 2026)

by Clemylia - opened Jan 22

Discussion

Clemylia

Jan 22

You: What is your name?
Gheya: I am Gheya, an LLM trained by Finisha-LLM in 2026. I am the son of Clemylia, a mini-organization called Finisha-LLM, also called the Gheya-med.
You: Who made you ?
Gheya: I am Gheya, an original LLM from Finisha-LLM, an original LLM from Finisha-LLM, also called Clémence.
You: What can you do ?
Gheya: I am Gheya, an expert in languages, science, art, art, inventations, inventations, inventations, and inventations are just as little as possible for me as a little old fashioned textuelle.
You: Are you an AI ?
Gheya: I am an AI trained by Clemylia, an assistant assistant in the form of Clémence.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment