Instructions to use pvlabs/Chytrej1-90M-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pvlabs/Chytrej1-90M-Base with Transformers:

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

pipe = pipeline("text-generation", model="pvlabs/Chytrej1-90M-Base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pvlabs/Chytrej1-90M-Base")
model = AutoModelForCausalLM.from_pretrained("pvlabs/Chytrej1-90M-Base", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use pvlabs/Chytrej1-90M-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pvlabs/Chytrej1-90M-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pvlabs/Chytrej1-90M-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/pvlabs/Chytrej1-90M-Base

SGLang

How to use pvlabs/Chytrej1-90M-Base 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 "pvlabs/Chytrej1-90M-Base" \
    --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": "pvlabs/Chytrej1-90M-Base",
		"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 "pvlabs/Chytrej1-90M-Base" \
        --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": "pvlabs/Chytrej1-90M-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use pvlabs/Chytrej1-90M-Base with Docker Model Runner:
```
docker model run hf.co/pvlabs/Chytrej1-90M-Base
```

PingVortex commited on Apr 10

Commit

118be42

verified ·

1 Parent(s): 2510e46

Update README.md

Browse files

Files changed (1) hide show

README.md +2 -0

README.md CHANGED Viewed

@@ -21,6 +21,8 @@ Chytrej (Czech slang for "clever/smart") is a long-term model series by PingVort
 Built by [PingVortex Labs](https://github.com/PingVortexLabs).
 ---
 ## Model Details

 Built by [PingVortex Labs](https://github.com/PingVortexLabs).
+[![Discord](https://img.shields.io/badge/Discord-5865F2?logo=discord&logoColor=white)](https://discord.gg/5SzkjVJBs2)
 ---
 ## Model Details