Text Generation
Transformers
PyTorch
Safetensors
English
custom_gpt
GPT
GPT-3 Small
GPT-3 Medium
GPT-3 Large
GPT-3 XL
GPT-3 2.7B
GPT-3 6.7B
GPT-3 13B
GPT-3 175B
GPT-3
GPT-2
GPT-2 124M
mit
HuggingFace
fineweb-edu
Decoder-Only
custom_code
Instructions to use samkeet/GPT_124M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samkeet/GPT_124M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="samkeet/GPT_124M", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("samkeet/GPT_124M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use samkeet/GPT_124M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "samkeet/GPT_124M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "samkeet/GPT_124M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/samkeet/GPT_124M
- SGLang
How to use samkeet/GPT_124M 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 "samkeet/GPT_124M" \ --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": "samkeet/GPT_124M", "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 "samkeet/GPT_124M" \ --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": "samkeet/GPT_124M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use samkeet/GPT_124M with Docker Model Runner:
docker model run hf.co/samkeet/GPT_124M
GitHub Link
Browse files
README.md
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- **Paper:** [Training Compute-Optimal Large Language Models](https://arxiv.org/pdf/2203.15556)
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- **Video:** [Andrej Karpathy-Let's reproduce GPT-2 (124M)](https://youtu.be/l8pRSuU81PU?si=KAo1y9dHYQAGJmj5)
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- **Demo:** [GPT 124M Demo](https://huggingface.co/spaces/samkeet/GPT_124M)
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## Model Details
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- **Paper:** [Training Compute-Optimal Large Language Models](https://arxiv.org/pdf/2203.15556)
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- **Video:** [Andrej Karpathy-Let's reproduce GPT-2 (124M)](https://youtu.be/l8pRSuU81PU?si=KAo1y9dHYQAGJmj5)
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- **Demo:** [GPT 124M Demo](https://huggingface.co/spaces/samkeet/GPT_124M)
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- **GitHub:** [SamkeetSangai/GPT_124M](https://github.com/SamkeetSangai/GPT_124M)
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## Model Details
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