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
File size: 724 Bytes
71dfa12 0f3e6c6 71dfa12 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"architectures": [
"GPTModelForTextGeneration"
],
"auto_map": {
"AutoConfig": "configuration_gpt.GPTConfig",
"AutoModelForCausalLM": "modeling_gpt.GPTModelForTextGeneration"
},
"block_size": 1024,
"custom_pipelines": {
"text-generation": {
"default": {
"model": {
"pt": "samkeet/GPT_124M"
}
},
"impl": "pipeline_gpt.GPT124MTextGenerationPipeline",
"pt": [
"AutoModelForCausalLM"
],
"tf": [],
"type": "text"
}
},
"model_type": "custom_gpt",
"n_embd": 768,
"n_head": 12,
"n_layer": 12,
"torch_dtype": "float32",
"transformers_version": "4.48.0",
"vocab_size": 50304
}
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