How to use James-WYang/BigTranslate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="James-WYang/BigTranslate")
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("James-WYang/BigTranslate") model = AutoModelForCausalLM.from_pretrained("James-WYang/BigTranslate")
How to use James-WYang/BigTranslate with vLLM:
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "James-WYang/BigTranslate" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "James-WYang/BigTranslate", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
docker model run hf.co/James-WYang/BigTranslate
How to use James-WYang/BigTranslate with SGLang:
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "James-WYang/BigTranslate" \ --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": "James-WYang/BigTranslate", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
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 "James-WYang/BigTranslate" \ --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": "James-WYang/BigTranslate", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
How to use James-WYang/BigTranslate with Docker Model Runner:
Hi authors,
Thank you very much for nice work on multilingual LLM!
I notice that you model is built on llama 13b, do you have 7b version?
I hope to follow your work but 13b is too large for me due to compute resource.
Thank you!
Best regards
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