Instructions to use AlgorithmicResearchGroup/gpt2-xs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlgorithmicResearchGroup/gpt2-xs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AlgorithmicResearchGroup/gpt2-xs")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/gpt2-xs") model = AutoModelForCausalLM.from_pretrained("AlgorithmicResearchGroup/gpt2-xs") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use AlgorithmicResearchGroup/gpt2-xs with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AlgorithmicResearchGroup/gpt2-xs" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AlgorithmicResearchGroup/gpt2-xs", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AlgorithmicResearchGroup/gpt2-xs
- SGLang
How to use AlgorithmicResearchGroup/gpt2-xs 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 "AlgorithmicResearchGroup/gpt2-xs" \ --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": "AlgorithmicResearchGroup/gpt2-xs", "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 "AlgorithmicResearchGroup/gpt2-xs" \ --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": "AlgorithmicResearchGroup/gpt2-xs", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AlgorithmicResearchGroup/gpt2-xs with Docker Model Runner:
docker model run hf.co/AlgorithmicResearchGroup/gpt2-xs
Matthew Kenney commited on
Commit ·
822993c
1
Parent(s): 1e30665
commit files to HF hub
Browse files- config.json +3 -3
- generation_config.json +1 -1
- model.safetensors +1 -1
config.json
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{
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"_name_or_path": "/content/2_vsmall_256_epoch_1e_3/checkpoint-
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"dropout": 0.
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.40.
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"use_cache": true,
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"vocab_size": 50257
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}
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{
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"_name_or_path": "/content/2_vsmall_256_epoch_1e_3/checkpoint-5000",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"bos_token_id": 50256,
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"dropout": 0.2,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.40.1",
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"use_cache": true,
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"vocab_size": 50257
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}
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generation_config.json
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.40.
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}
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.40.1"
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}
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model.safetensors
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