Instructions to use Toflamus/Finetuned3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Toflamus/Finetuned3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Toflamus/Finetuned3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Toflamus/Finetuned3") model = AutoModelForCausalLM.from_pretrained("Toflamus/Finetuned3") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Toflamus/Finetuned3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Toflamus/Finetuned3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Toflamus/Finetuned3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Toflamus/Finetuned3
- SGLang
How to use Toflamus/Finetuned3 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 "Toflamus/Finetuned3" \ --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": "Toflamus/Finetuned3", "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 "Toflamus/Finetuned3" \ --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": "Toflamus/Finetuned3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Toflamus/Finetuned3 with Docker Model Runner:
docker model run hf.co/Toflamus/Finetuned3
Update README.md
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README.md
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# Output
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This model is a fine-tuned version of [Toflamus/GPT-2_para3M](https://huggingface.co/Toflamus/GPT-2_para3M) on an unknown dataset.
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## Model description
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More information needed
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- num_epochs: 5
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### Training results
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### Framework versions
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# Output
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This model is a fine-tuned version of [Toflamus/GPT-2_para3M](https://huggingface.co/Toflamus/GPT-2_para3M) on an unknown dataset.
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TrainOutput(global_step=4060, training_loss=6.123095868491187, metrics={'train_runtime': 1435.0504, 'train_samples_per_second': 181.185, 'train_steps_per_second': 2.829, 'total_flos': 96669633527808.0, 'train_loss': 6.123095868491187, 'epoch': 5.0})
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## Model description
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More information needed
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- num_epochs: 5
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### Training results
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Step Training Loss
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100 7.737900
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200 7.066700
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300 6.840200
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+
400 6.686600
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+
500 6.607700
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+
600 6.516500
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+
700 6.449800
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+
800 6.360400
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+
900 6.321700
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+
1000 6.252700
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1100 6.223500
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1200 6.194700
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1300 6.131500
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1400 6.113400
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1500 6.106500
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+
1600 6.044100
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1700 6.024400
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1800 6.008500
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1900 6.006600
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2000 5.959900
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2100 5.931100
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2200 5.925300
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2300 5.933500
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2400 5.921900
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2500 5.913400
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2600 5.898100
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2700 5.874700
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2800 5.869100
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2900 5.851200
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3000 5.853900
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3100 5.870100
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3200 5.868100
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3300 5.837000
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3400 5.845300
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3500 5.828800
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3600 5.847400
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3700 5.858600
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3800 5.853200
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3900 5.836600
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4000 5.849100
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### Framework versions
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