Text Generation
Transformers
PyTorch
Safetensors
English
babylang
gpt
transformer
small-model
from-scratch
babymodel
custom_code
Instructions to use Exquisique/BabyLangModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Exquisique/BabyLangModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Exquisique/BabyLangModel", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Exquisique/BabyLangModel", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Exquisique/BabyLangModel with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Exquisique/BabyLangModel" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Exquisique/BabyLangModel", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Exquisique/BabyLangModel
- SGLang
How to use Exquisique/BabyLangModel 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 "Exquisique/BabyLangModel" \ --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": "Exquisique/BabyLangModel", "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 "Exquisique/BabyLangModel" \ --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": "Exquisique/BabyLangModel", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Exquisique/BabyLangModel with Docker Model Runner:
docker model run hf.co/Exquisique/BabyLangModel
Commit History
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Update README.md
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (b808ca9dec6e78d605287828fcf35255615b2424) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>bbd1dcc
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Update pytorch_model.bin with extracted model weights
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Configure custom GPT for AutoModel loading
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Updated model.py to work with AutoModel and trust_remote_code
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Make GPT inherit from PreTrainedModel for HF compatibility
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Add model card metadata for HuggingFace tags
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Upload BabyLangModel with model card and config
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initial commit
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