Instructions to use microsoft/phi-1_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/phi-1_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="microsoft/phi-1_5")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-1_5") model = AutoModelForCausalLM.from_pretrained("microsoft/phi-1_5") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use microsoft/phi-1_5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "microsoft/phi-1_5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "microsoft/phi-1_5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/microsoft/phi-1_5
- SGLang
How to use microsoft/phi-1_5 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 "microsoft/phi-1_5" \ --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": "microsoft/phi-1_5", "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 "microsoft/phi-1_5" \ --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": "microsoft/phi-1_5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use microsoft/phi-1_5 with Docker Model Runner:
docker model run hf.co/microsoft/phi-1_5
Integration in transformers lib.
When do you plan to integrate in transformers lib as a pipeline function ?
On behalf of the transformers team, we'd be happy to help with the integration within the library if there is desire from @gugarosa or @suriyagunasekar π€
Thank you !!
Will it support fine-tuning these models, such as phi-1 and phi-1.5?
Currently, during my finetuning, I encountered this warning
`attention_mask` is not supported during training. Using it might lead to unexpected results.
{'loss': 1.3228, 'learning_rate': 1.999875577156579e-05, 'epoch': 0.02}
1%|β | 300/59745 [06:19<20:47:29, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 301/59745 [06:20<20:48:14, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 302/59745 [06:22<20:48:01, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 303/59745 [06:23<20:47:31, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 304/59745 [06:24<20:48:13, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 305/59745 [06:25<20:49:27, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 306/59745 [06:27<20:48:52, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 307/59745 [06:28<20:48:29, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 308/59745 [06:29<20:49:14, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
1%|β | 309/59745 [06:30<20:49:49, 1.26s/it]`attention_mask` is not supported during training. Using it might lead to unexpected results.
{'loss': 1.5263, 'learning_rate': 1.9998671442394832e-05, 'epoch': 0.02}
Hello @SinclairWang ! Until phi is fully integrated in transformers, we added support for training/fine-tuning with attention mask in the files located in this repository.
You should not get the warning anymore if using the latest revision.