Instructions to use hf-internal-testing/tiny-xlm-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hf-internal-testing/tiny-xlm-roberta with Transformers:

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

pipe = pipeline("text-generation", model="hf-internal-testing/tiny-xlm-roberta")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-xlm-roberta")
model = AutoModelForCausalLM.from_pretrained("hf-internal-testing/tiny-xlm-roberta", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use hf-internal-testing/tiny-xlm-roberta with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/hf-internal-testing/tiny-xlm-roberta

SGLang

How to use hf-internal-testing/tiny-xlm-roberta 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 "hf-internal-testing/tiny-xlm-roberta" \
    --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": "hf-internal-testing/tiny-xlm-roberta",
		"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 "hf-internal-testing/tiny-xlm-roberta" \
        --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": "hf-internal-testing/tiny-xlm-roberta",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use hf-internal-testing/tiny-xlm-roberta with Docker Model Runner:
```
docker model run hf.co/hf-internal-testing/tiny-xlm-roberta
```

stas commited on Jul 8, 2021

Commit

6eaa078

1 Parent(s): 608ea72

extra

Browse files

Files changed (1) hide show

make-tiny-xlm-roberta.py +6 -2

make-tiny-xlm-roberta.py CHANGED Viewed

@@ -34,10 +34,14 @@
 # wget https://huggingface.co/hf-internal-testing/tiny-bert/raw/main/make-tiny-xlm-roberta.py
 # chmod a+x ./make-tiny-xlm-roberta.py
 #
-# 5. edit and re-run this script while fixing it up
 # ./make-tiny-xlm-roberta.py .
 #
-# 6. add/commit/push
 # git add *
 # git commit -m "new tiny model"
 # git push

 # wget https://huggingface.co/hf-internal-testing/tiny-bert/raw/main/make-tiny-xlm-roberta.py
 # chmod a+x ./make-tiny-xlm-roberta.py
 #
+# 5. automatically rename things from the old names to new ones
+# perl -pi -e 's|MT5|XLMRoberta|g' make-tiny-xlm-roberta.py
+# perl -pi -e 's|mt5|xlm-roberta|g' make-tiny-xlm-roberta.py
+#
+# 6. edit and re-run this script while fixing it up
 # ./make-tiny-xlm-roberta.py .
 #
+# 7. add/commit/push
 # git add *
 # git commit -m "new tiny model"
 # git push