Instructions to use Adeptschneider/llama3-civivox-english-to-swahili-translation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adeptschneider/llama3-civivox-english-to-swahili-translation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Adeptschneider/llama3-civivox-english-to-swahili-translation")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Adeptschneider/llama3-civivox-english-to-swahili-translation") model = AutoModelForCausalLM.from_pretrained("Adeptschneider/llama3-civivox-english-to-swahili-translation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Adeptschneider/llama3-civivox-english-to-swahili-translation with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Adeptschneider/llama3-civivox-english-to-swahili-translation" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Adeptschneider/llama3-civivox-english-to-swahili-translation", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Adeptschneider/llama3-civivox-english-to-swahili-translation
- SGLang
How to use Adeptschneider/llama3-civivox-english-to-swahili-translation 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 "Adeptschneider/llama3-civivox-english-to-swahili-translation" \ --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": "Adeptschneider/llama3-civivox-english-to-swahili-translation", "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 "Adeptschneider/llama3-civivox-english-to-swahili-translation" \ --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": "Adeptschneider/llama3-civivox-english-to-swahili-translation", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Desktop
- Docker Model Runner
How to use Adeptschneider/llama3-civivox-english-to-swahili-translation with Docker Model Runner:
docker model run hf.co/Adeptschneider/llama3-civivox-english-to-swahili-translation
Download model-00002-of-00002.safetensors from Adeptschneider/llama3-civivox-english-to-swahili-translation: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/Adeptschneider/llama3-civivox-english-to-swahili-translation/resolve/main/model-00002-of-00002.safetensors
- Command line
-
hf download hf://Adeptschneider/llama3-civivox-english-to-swahili-translation/model-00002-of-00002.safetensors
-
curl -L -o model-00002-of-00002.safetensors https://huggingface.co/Adeptschneider/llama3-civivox-english-to-swahili-translation/resolve/main/model-00002-of-00002.safetensors
1.46 GB
- Xet hash:
- 3c61ba003a9f698997a8e07b1ac6e865ef59d85e21fdf75dc2021d0b1b962040
- Size of remote file:
- 1.46 GB
- SHA256:
- 03c374364705c14e03150dbe976758431dff730d11bd719a57bcc61098333014
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