Instructions to use cs-552-2026-catma/multilingual_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cs-552-2026-catma/multilingual_model with Transformers:

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

pipe = pipeline("text-generation", model="cs-552-2026-catma/multilingual_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cs-552-2026-catma/multilingual_model")
model = AutoModelForCausalLM.from_pretrained("cs-552-2026-catma/multilingual_model", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cs-552-2026-catma/multilingual_model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cs-552-2026-catma/multilingual_model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cs-552-2026-catma/multilingual_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cs-552-2026-catma/multilingual_model

SGLang

How to use cs-552-2026-catma/multilingual_model 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 "cs-552-2026-catma/multilingual_model" \
    --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": "cs-552-2026-catma/multilingual_model",
		"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 "cs-552-2026-catma/multilingual_model" \
        --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": "cs-552-2026-catma/multilingual_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cs-552-2026-catma/multilingual_model with Docker Model Runner:
```
docker model run hf.co/cs-552-2026-catma/multilingual_model
```

multilingual_model

Commit History

Update Automated MNLP evaluation report (2026-05-19)

ce914fc
verified

zechen-nlp commited on May 19

Automated MNLP evaluation report (2026-05-18)

ac440fb
verified

zechen-nlp commited on May 18

Automated MNLP evaluation report (2026-05-17) (#4)

dfd7172

cristiano-masutti

zechen-nlp commited on May 17

Upload tokenizer

aa74e02
verified

mariem38 commited on May 17

Upload Qwen3ForCausalLM

4e2ba90
verified

mariem38 commited on May 17

Automated MNLP evaluation report (2026-05-16) (#3)

f031775

mariem38

zechen-nlp commited on May 16

Automated MNLP evaluation report (2026-05-13) (#2)

9a45bbc

cristiano-masutti

zechen-nlp commited on May 15

Upload tokenizer

131adac
verified

TuanNguyen2003 commited on May 14

Upload Qwen3ForCausalLM

0417c60
verified

TuanNguyen2003 commited on May 14

Automated MNLP evaluation report (2026-05-13) (#1)

a528993

cristiano-masutti

zechen-nlp commited on May 13

Upload folder using huggingface_hub

c4ae390
verified

cristiano-masutti commited on May 7

initial commit

aea74ed
verified

cristiano-masutti commited on May 4

Commit History

Update Automated MNLP evaluation report (2026-05-19) ce914fc verified

Automated MNLP evaluation report (2026-05-18) ac440fb verified

Automated MNLP evaluation report (2026-05-17) (#4) dfd7172

Upload tokenizer aa74e02 verified

Upload Qwen3ForCausalLM 4e2ba90 verified

Automated MNLP evaluation report (2026-05-16) (#3) f031775

Automated MNLP evaluation report (2026-05-13) (#2) 9a45bbc

Upload tokenizer 131adac verified

Upload Qwen3ForCausalLM 0417c60 verified

Automated MNLP evaluation report (2026-05-13) (#1) a528993

Upload folder using huggingface_hub c4ae390 verified

initial commit aea74ed verified

Update Automated MNLP evaluation report (2026-05-19)

ce914fc
verified

Automated MNLP evaluation report (2026-05-18)

ac440fb
verified

Automated MNLP evaluation report (2026-05-17) (#4)

dfd7172

Upload tokenizer

aa74e02
verified

Upload Qwen3ForCausalLM

4e2ba90
verified

Automated MNLP evaluation report (2026-05-16) (#3)

f031775

Automated MNLP evaluation report (2026-05-13) (#2)

9a45bbc

Upload tokenizer

131adac
verified

Upload Qwen3ForCausalLM

0417c60
verified

Automated MNLP evaluation report (2026-05-13) (#1)

a528993

Upload folder using huggingface_hub

c4ae390
verified

initial commit

aea74ed
verified