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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TroyDoesAI/MermaidSolar") model = AutoModelForCausalLM.from_pretrained("TroyDoesAI/MermaidSolar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
Commit History
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Upload example_of_how_to_use_my_model_requires_response_to_include_the_cue_tripleTicknewlinegraph_then_LR_RL_TD_TB_to_select_various_types_of_graphs_it_knows.txt
Verified signatureHow to use my model, please ensure the response includes " ### Response: ```mermaid graph TB " 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.829a2a0 -
Example Provided on how to use my Model. Note: The dataset does not consist of anything but Python examples, so this is fun trying bash and things it generalized on its own. AI is beautiful!
Verified signatureUse this as an example of how to use my Models. The explanation of the models is in the other model cards such as MermaidMistrale18bcfd
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Verified signatureIncomplete: 3 Epoch ~ Still improving on same hand crafted dataset This is only a checkpoint: Eval loss continues to decrease.93d388b -
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Verified signatureIncomplete Model: 2 Epoch Of My Hand Crafted DataSet ~ Still Improving Performance TODO: Compare [MermaidSolar 10.7B] to [MermaidMistral 7B DPO] my current best model.8404781
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Verified signatureIncomplete Model : Testing 1 Epoch Full Tune on my hand crafted datasete44099d -
initial commit
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