Instructions to use EuSheriff/Biticonha_bot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EuSheriff/Biticonha_bot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="EuSheriff/Biticonha_bot")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("EuSheriff/Biticonha_bot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use EuSheriff/Biticonha_bot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EuSheriff/Biticonha_bot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EuSheriff/Biticonha_bot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EuSheriff/Biticonha_bot
- SGLang
How to use EuSheriff/Biticonha_bot 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 "EuSheriff/Biticonha_bot" \ --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": "EuSheriff/Biticonha_bot", "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 "EuSheriff/Biticonha_bot" \ --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": "EuSheriff/Biticonha_bot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use EuSheriff/Biticonha_bot with Docker Model Runner:
docker model run hf.co/EuSheriff/Biticonha_bot
language: en license: openrail datasets:
- "Você pode adicionar o nome de seu dataset aqui, se aplicável" metrics:
- "Você pode adicionar as métricas que você usou para avaliar o modelo aqui" model_name: "Biticonha AI Trader Pro" pipeline_tag: text-generation license: MIT task:
- text-generation description: | The Biticonha AI Trader Pro model is a GPT-based trading assistant that provides real-time trading signals based on various technical indicators, such as the Relative Strength Index (RSI), to help traders make informed decisions in the cryptocurrency market.
This model is designed to generate buy/sell signals for popular cryptocurrency pairs such as BTC/USDT, ETH/USDT, and others based on the analysis of market data. It uses natural language processing techniques to interpret trading signals from raw market data, delivering easy-to-understand advice for both beginners and advanced traders.
The model can be integrated into Telegram bots, where it sends buy and sell signals to trading groups or individual users.
Example usage: Ask the model to generate buy signals based on market indicators such as RSI.
tags: - Trading - AI - Crypto - Signals - Cryptocurrency - TradingBot - GPT - MarketAnalysis - TradingSignals
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