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, device_map="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
Upload tokenizer
Browse files- special_tokens_map.json +23 -1
- tokenizer_config.json +6 -2
special_tokens_map.json
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"bos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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"eos_token": {
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"content": "<|endoftext|>",
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tokenizer_config.json
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"clean_up_tokenization_spaces": false,
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"content": "<|endoftext|>",
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"special": true
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|endoftext|>",
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"extra_special_tokens": {},
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"model_max_length": 1024,
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": "<|endoftext|>"
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