Text Generation
Transformers
TensorBoard
Safetensors
gpt2
Generated from Trainer
text-generation-inference
Instructions to use GPT-JF/Model_1A_Clinton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GPT-JF/Model_1A_Clinton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GPT-JF/Model_1A_Clinton")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("GPT-JF/Model_1A_Clinton") model = AutoModelForCausalLM.from_pretrained("GPT-JF/Model_1A_Clinton") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use GPT-JF/Model_1A_Clinton with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GPT-JF/Model_1A_Clinton" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GPT-JF/Model_1A_Clinton", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GPT-JF/Model_1A_Clinton
- SGLang
How to use GPT-JF/Model_1A_Clinton 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 "GPT-JF/Model_1A_Clinton" \ --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": "GPT-JF/Model_1A_Clinton", "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 "GPT-JF/Model_1A_Clinton" \ --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": "GPT-JF/Model_1A_Clinton", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GPT-JF/Model_1A_Clinton with Docker Model Runner:
docker model run hf.co/GPT-JF/Model_1A_Clinton
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README.md
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# Model_1A_Clinton
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This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on
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##
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## Intended uses & limitations
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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- lr_scheduler_type: linear
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- num_epochs: 5.0
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### Training results
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### Framework versions
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- Transformers 4.35.2
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# Model_1A_Clinton
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This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on a large corpus of William J. Clinton's second term discourse on terrorism.
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## To Prompt the Model
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Try entering single words or short phrases, such as "terrorism is" or "national security" or "our foreign policy should be",
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in the dialogue box on the right hand side of this page.
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Then click on 'compute' and wait for the results. The model will take a few seconds to load on your first prompt.
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## Intended uses & limitations
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This model is intended as an experiment on the utility of LLMs for discourse analysis on a specific corpus of political rhetoric.
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### Training hyperparameters
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- lr_scheduler_type: linear
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- num_epochs: 5.0
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### Framework versions
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- Transformers 4.35.2
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