Instructions to use TroyDoesAI/MermaidSolar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TroyDoesAI/MermaidSolar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TroyDoesAI/MermaidSolar")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TroyDoesAI/MermaidSolar") model = AutoModelForCausalLM.from_pretrained("TroyDoesAI/MermaidSolar") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TroyDoesAI/MermaidSolar with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TroyDoesAI/MermaidSolar" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TroyDoesAI/MermaidSolar", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TroyDoesAI/MermaidSolar
- SGLang
How to use TroyDoesAI/MermaidSolar 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 "TroyDoesAI/MermaidSolar" \ --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": "TroyDoesAI/MermaidSolar", "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 "TroyDoesAI/MermaidSolar" \ --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": "TroyDoesAI/MermaidSolar", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TroyDoesAI/MermaidSolar with Docker Model Runner:
docker model run hf.co/TroyDoesAI/MermaidSolar
Update README.md
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README.md
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See Model Card from MermaidMistral or MermaidLLama or MermaidStable3B for more information, this is the same dataset applied to the Solar 10.7B Base Model,
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Interesting findings is that the hand curated 800 examples I made of as diverse edge cases I could come up with seem to still improve the models ability,
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Which shows both in the training loss and eval loss trends as they continue to get closer to 0 together, with the eval loss at roughly the same as training loss values.
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See Model Card from MermaidMistral or MermaidLLama or MermaidStable3B for more information, this is the same dataset applied to the Solar 10.7B Base Model,
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How to use my model, please ensure the response includes
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### Response:
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```mermaid\n
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graph TB
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It is critical because I have it trained to work in my pipeline that anytime I put "```mermaid" it knows to create a mermaid block of anything in its context.
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Interesting findings is that the hand curated 800 examples I made of as diverse edge cases I could come up with seem to still improve the models ability,
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Which shows both in the training loss and eval loss trends as they continue to get closer to 0 together, with the eval loss at roughly the same as training loss values.
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