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

Libraries

How to use nkuAlexLee/Pokemon_EN_to_ZH with Transformers:

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

pipe = pipeline("text-generation", model="nkuAlexLee/Pokemon_EN_to_ZH")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("nkuAlexLee/Pokemon_EN_to_ZH")
model = AutoModelForSeq2SeqLM.from_pretrained("nkuAlexLee/Pokemon_EN_to_ZH", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nkuAlexLee/Pokemon_EN_to_ZH with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/nkuAlexLee/Pokemon_EN_to_ZH

SGLang

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

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

Pokemon_EN_to_ZH / training_args.bin

nkuAlexLee

Upload 13 files

334667b over 3 years ago

Download

History Blame Contribute Delete

4.03 kB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: 244e548d02b625d41032da868609d696824f2458c246924a23e76ff393e97564
Size of remote file:: 4.03 kB
SHA256:: 093ba43f3bf932ee2c0a0909229582d9d4b5b60aa73b0d1fe5caf0a48ad77ddb

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.