Instructions to use 01-ai/Yi-34B-200K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 01-ai/Yi-34B-200K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="01-ai/Yi-34B-200K")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("01-ai/Yi-34B-200K") model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-34B-200K") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 01-ai/Yi-34B-200K with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "01-ai/Yi-34B-200K" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "01-ai/Yi-34B-200K", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/01-ai/Yi-34B-200K
- SGLang
How to use 01-ai/Yi-34B-200K 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 "01-ai/Yi-34B-200K" \ --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": "01-ai/Yi-34B-200K", "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 "01-ai/Yi-34B-200K" \ --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": "01-ai/Yi-34B-200K", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 01-ai/Yi-34B-200K with Docker Model Runner:
docker model run hf.co/01-ai/Yi-34B-200K
update README and logo
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README.md
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The **Yi** series models are large language models trained from scratch by
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developers at [01.AI](https://01.ai/). The first public release contains two
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bilingual(English/Chinese) base models with the parameter sizes of 6B
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Both of them are trained with 4K sequence length and can be
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during inference time.
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## News
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- 🎯 **2023/11/05**: The base model of
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- 🎯 **2023/11/02**: The base model of `Yi-6B` and `Yi-34B`.
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The **Yi** series models are large language models trained from scratch by
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developers at [01.AI](https://01.ai/). The first public release contains two
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bilingual(English/Chinese) base models with the parameter sizes of 6B(`Yi-6B`)
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and 34B(`Yi-34B`). Both of them are trained with 4K sequence length and can be
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extended to 32K during inference time. The `Yi-6B-200K` and `Yi-34B-200K` are
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base model with 200K context length.
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## News
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- 🎯 **2023/11/05**: The base model of `Yi-6B-200K` and `Yi-34B-200K` with 200K context length.
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- 🎯 **2023/11/02**: The base model of `Yi-6B` and `Yi-34B`.
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Yi.svg
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