Instructions to use 01-ai/Yi-34B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 01-ai/Yi-34B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="01-ai/Yi-34B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("01-ai/Yi-34B") model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-34B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use 01-ai/Yi-34B 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" # 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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/01-ai/Yi-34B
- SGLang
How to use 01-ai/Yi-34B 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" \ --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", "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" \ --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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 01-ai/Yi-34B with Docker Model Runner:
docker model run hf.co/01-ai/Yi-34B
fine-tuning with autotrain-advanced
Hi I was trying to fine tune this model with autotrain advanced, but I face this exception:
out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = flash_attn_cuda.fwd(
RuntimeError: FlashAttention only support fp16 and bf16 data type
this is my command:
autotrain llm --train --project_name deacon-34b --model /run/media/knut/HD2/Yi-34B/ --data_path . --train_batch_size 1 --num_train_epochs 5 --trainer sft --use_int4 --use_peft --merge_adapter --target_modules "q_proj,k_proj,v_proj,o_proj"
I tried to reinstall a few libs, but could not resolve it. Is it already possible to fine tune your model with hf autotrain-advanced?
When loading the model, considering add torch_type='auto' in the model_class.from_pretrained API
I'm trying this with 4bit or 8bit peft fine tuning. I hacked around both in the models python files and in the main.py of autotrain-advanced, tried to add toch_dtype='auto' where I could see it might work. So far I had no luck. https://github.com/huggingface/autotrain-advanced/blob/main/src/autotrain/trainers/clm/__main__.py
I will close this.Please help make peft fine tuning with hf transformers work.
Please help make peft fine tuning with hf transformers work.
Will do!
And please watch our github repo for the latest progress. 🤗