Instructions to use phonemetransformers/childes-segmentation-random-gpt2_lm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use phonemetransformers/childes-segmentation-random-gpt2_lm-model with Transformers:

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

pipe = pipeline("text-generation", model="phonemetransformers/childes-segmentation-random-gpt2_lm-model")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("phonemetransformers/childes-segmentation-random-gpt2_lm-model")
model = AutoModelForCausalLM.from_pretrained("phonemetransformers/childes-segmentation-random-gpt2_lm-model", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use phonemetransformers/childes-segmentation-random-gpt2_lm-model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "phonemetransformers/childes-segmentation-random-gpt2_lm-model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "phonemetransformers/childes-segmentation-random-gpt2_lm-model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/phonemetransformers/childes-segmentation-random-gpt2_lm-model

SGLang

How to use phonemetransformers/childes-segmentation-random-gpt2_lm-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 "phonemetransformers/childes-segmentation-random-gpt2_lm-model" \
    --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": "phonemetransformers/childes-segmentation-random-gpt2_lm-model",
		"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 "phonemetransformers/childes-segmentation-random-gpt2_lm-model" \
        --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": "phonemetransformers/childes-segmentation-random-gpt2_lm-model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use phonemetransformers/childes-segmentation-random-gpt2_lm-model with Docker Model Runner:
```
docker model run hf.co/phonemetransformers/childes-segmentation-random-gpt2_lm-model
```

childes-segmentation-random-gpt2_lm-model / vocab.json

codebyzeb

Training in progress, step 20000

bba9867 verified over 1 year ago

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{"UNK":0,"PAD":1,"WORD_BOUNDARY":2,"UTT_BOUNDARY":3,"d̠ʒ":4,"ʌ":5,"s":6,"t":7,"l":8,"aɪ":9,"k":10,"j":11,"ʊ":12,"ɹ":13,"b":14,"æ":15,"h":16,"oʊ":17,"m":18,"iː":19,"ð":20,"ɛ":21,"z":22,"f":23,"eɪ":24,"w":25,"ɪ":26,"ɡ":27,"ɑ":28,"ə":29,"p":30,"uː":31,"i":32,"θ":33,"ŋ":34,"ɔ":35,"ɔɪ":36,"n":37,"d":38,"aʊ":39,"v":40,"ɜː":41,"t̠ʃ":42,"ʃ":43,"iə":44,"ʒ":45,"x":46}