Instructions to use cfli/LLARA-document with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cfli/LLARA-document with Transformers:

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

pipe = pipeline("text-generation", model="cfli/LLARA-document")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cfli/LLARA-document")
model = AutoModelForCausalLM.from_pretrained("cfli/LLARA-document", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cfli/LLARA-document with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/cfli/LLARA-document

SGLang

How to use cfli/LLARA-document 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 "cfli/LLARA-document" \
    --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": "cfli/LLARA-document",
		"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 "cfli/LLARA-document" \
        --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": "cfli/LLARA-document",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use cfli/LLARA-document with Docker Model Runner:
```
docker model run hf.co/cfli/LLARA-document
```

LLARA-document

File size: 282 Bytes

9878e38

{
  "<s10>": 32009,
  "<s11>": 32012,
  "<s12>": 32001,
  "<s13>": 32010,
  "<s14>": 32003,
  "<s15>": 32006,
  "<s16>": 32015,
  "<s1>": 32008,
  "<s2>": 32011,
  "<s3>": 32004,
  "<s4>": 32013,
  "<s5>": 32007,
  "<s6>": 32005,
  "<s7>": 32002,
  "<s8>": 32014,
  "<s9>": 32000
}