Instructions to use FlyLee/bayesian-peft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FlyLee/bayesian-peft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FlyLee/bayesian-peft")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FlyLee/bayesian-peft", dtype="auto") - PEFT
How to use FlyLee/bayesian-peft with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use FlyLee/bayesian-peft with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FlyLee/bayesian-peft" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FlyLee/bayesian-peft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FlyLee/bayesian-peft
- SGLang
How to use FlyLee/bayesian-peft 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 "FlyLee/bayesian-peft" \ --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": "FlyLee/bayesian-peft", "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 "FlyLee/bayesian-peft" \ --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": "FlyLee/bayesian-peft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FlyLee/bayesian-peft with Docker Model Runner:
docker model run hf.co/FlyLee/bayesian-peft
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,13 @@
|
|
| 1 |
-
---
|
| 2 |
-
license: llama3.1
|
| 3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: llama3.1
|
| 3 |
+
datasets:
|
| 4 |
+
- allenai/winogrande
|
| 5 |
+
- allenai/ai2_arc
|
| 6 |
+
- google/boolq
|
| 7 |
+
- wentingzhao/obqa
|
| 8 |
+
base_model:
|
| 9 |
+
- meta-llama/Llama-3.1-8B
|
| 10 |
+
tags:
|
| 11 |
+
- peft
|
| 12 |
+
- bayesian
|
| 13 |
+
---
|