Instructions to use evilfreelancer/ruGPT3XL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use evilfreelancer/ruGPT3XL with Transformers:

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

pipe = pipeline("text-generation", model="evilfreelancer/ruGPT3XL", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("evilfreelancer/ruGPT3XL", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use evilfreelancer/ruGPT3XL with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "evilfreelancer/ruGPT3XL"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "evilfreelancer/ruGPT3XL",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/evilfreelancer/ruGPT3XL

SGLang

How to use evilfreelancer/ruGPT3XL 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 "evilfreelancer/ruGPT3XL" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "evilfreelancer/ruGPT3XL",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "evilfreelancer/ruGPT3XL" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "evilfreelancer/ruGPT3XL",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use evilfreelancer/ruGPT3XL with Docker Model Runner:
```
docker model run hf.co/evilfreelancer/ruGPT3XL
```

Pavel Rykov commited on Mar 27

Commit

511ef2e

1 Parent(s): d01e7f2

Typo fix

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -21,7 +21,7 @@ into a native HuggingFace `transformers` format.
 This is a **base (pretrained) model**, not instruction-tuned. It performs text completion
 and can be fine-tuned for downstream tasks.
-See more in "[A family of pretrained transformer language models for Russian](https://scholar.google.com/citations?view_op=view_citation&hl=en&user=yPayeJIAAAAJ&citation_for_view=yPayeJIAAAAJ:Se3iqnhoufwC)" paper.
 ## Model Details
@@ -280,7 +280,7 @@ For full conversion details and the script, see the
 ```bibtex
 @misc{rugpt3xl,
-  title={ruGPT3XL-GGUF},
   author={Pavel Rykov},
   year={2026},
   publisher={Hugging Face},

 This is a **base (pretrained) model**, not instruction-tuned. It performs text completion
 and can be fine-tuned for downstream tasks.
+Details in "[A family of pretrained transformer language models for Russian](https://scholar.google.com/citations?view_op=view_citation&hl=en&user=yPayeJIAAAAJ&citation_for_view=yPayeJIAAAAJ:Se3iqnhoufwC)" paper.
 ## Model Details
 ```bibtex
 @misc{rugpt3xl,
+  title={ruGPT3XL},
   author={Pavel Rykov},
   year={2026},
   publisher={Hugging Face},