Instructions to use ltg/deberta-xxlarge-fixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltg/deberta-xxlarge-fixed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ltg/deberta-xxlarge-fixed", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ltg/deberta-xxlarge-fixed", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ltg/deberta-xxlarge-fixed with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ltg/deberta-xxlarge-fixed" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ltg/deberta-xxlarge-fixed", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ltg/deberta-xxlarge-fixed
- SGLang
How to use ltg/deberta-xxlarge-fixed 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 "ltg/deberta-xxlarge-fixed" \ --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": "ltg/deberta-xxlarge-fixed", "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 "ltg/deberta-xxlarge-fixed" \ --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": "ltg/deberta-xxlarge-fixed", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ltg/deberta-xxlarge-fixed with Docker Model Runner:
docker model run hf.co/ltg/deberta-xxlarge-fixed
Update README.md
Browse files
README.md
CHANGED
|
@@ -50,14 +50,13 @@ print(prediction)
|
|
| 50 |
If you find DeBERTa useful for your work, please cite the following paper:
|
| 51 |
|
| 52 |
```bibtex
|
| 53 |
-
@
|
| 54 |
-
|
|
|
|
| 55 |
author={David Samuel},
|
|
|
|
| 56 |
year={2024},
|
| 57 |
-
|
| 58 |
-
archivePrefix={arXiv},
|
| 59 |
-
primaryClass={cs.CL},
|
| 60 |
-
url={https://arxiv.org/abs/2406.04823}
|
| 61 |
}
|
| 62 |
```
|
| 63 |
|
|
|
|
| 50 |
If you find DeBERTa useful for your work, please cite the following paper:
|
| 51 |
|
| 52 |
```bibtex
|
| 53 |
+
@inproceedings{
|
| 54 |
+
samuel2024berts,
|
| 55 |
+
title={{BERT}s are Generative In-Context Learners},
|
| 56 |
author={David Samuel},
|
| 57 |
+
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
|
| 58 |
year={2024},
|
| 59 |
+
url={https://openreview.net/forum?id=BCA9NMZkLS}
|
|
|
|
|
|
|
|
|
|
| 60 |
}
|
| 61 |
```
|
| 62 |
|