Instructions to use dev2bit/es2bash-mt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dev2bit/es2bash-mt5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dev2bit/es2bash-mt5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dev2bit/es2bash-mt5") model = AutoModelForSeq2SeqLM.from_pretrained("dev2bit/es2bash-mt5") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dev2bit/es2bash-mt5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dev2bit/es2bash-mt5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dev2bit/es2bash-mt5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dev2bit/es2bash-mt5
- SGLang
How to use dev2bit/es2bash-mt5 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 "dev2bit/es2bash-mt5" \ --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": "dev2bit/es2bash-mt5", "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 "dev2bit/es2bash-mt5" \ --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": "dev2bit/es2bash-mt5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dev2bit/es2bash-mt5 with Docker Model Runner:
docker model run hf.co/dev2bit/es2bash-mt5
Commit ·
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Parent(s): eaa1282
Update README.md
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README.md
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pipeline_tag: text2text-generation
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tags:
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- code
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---
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# es2bash-mt5: Modelo de traducción de español a Bashcd
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pipeline_tag: text2text-generation
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tags:
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- code
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- bash
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widget:
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- text: Muestra el contenido de file.py que se encuentra en home
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example_title: cat
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- text: Lista el directorio actual ordenado por tamaño de ficheros
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example_title: ls
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- text: Directorio de configuración de varnish
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example_title: cd
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- text: Lista todos los átomos del universo
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example_title: noCommand
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- text: ls -lh
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example_title: literal
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- text: file.txt
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example_title: simple
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---
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# es2bash-mt5: Modelo de traducción de español a Bashcd
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