Instructions to use antiven0m/peccadillo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antiven0m/peccadillo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="antiven0m/peccadillo")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("antiven0m/peccadillo") model = AutoModelForCausalLM.from_pretrained("antiven0m/peccadillo") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use antiven0m/peccadillo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "antiven0m/peccadillo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "antiven0m/peccadillo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/antiven0m/peccadillo
- SGLang
How to use antiven0m/peccadillo 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 "antiven0m/peccadillo" \ --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": "antiven0m/peccadillo", "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 "antiven0m/peccadillo" \ --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": "antiven0m/peccadillo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use antiven0m/peccadillo with Docker Model Runner:
docker model run hf.co/antiven0m/peccadillo
Librarian Bot: Add base_model metadata to model
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README.md
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```yaml
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models:
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- model: mistralai/Mistral-7B-v0.1
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---
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base_model:
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- mistralai/Mistral-7B-v0.1
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- rwitz2/go-bruins-v2.1.1
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- athirdpath/NSFW_DPO_vmgb-7b
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- openerotica/cockatrice-7b-v0.1
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- segmed/MedMistral-7B-v0.1
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---
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```yaml
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models:
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- model: mistralai/Mistral-7B-v0.1
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