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
GSM8K scores after the 2024-03march update
#21
by CombinHorizon - opened
Hi,
after the change to improve its haystack-retrieval scores,
its math GSM8K scores have dropped from
61.6% (before), to 34.9% after the update
reference:
https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/01-ai/Yi-34B-200K/results_2023-12-05T03-41-41.478096.json
https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/01-ai/Yi-34B-200K/results_2024-04-16T04-20-00.686323.json
what could be the cause of this?
how would (or will) this be addressed, will there be a future update ?