Instructions to use GItaf/bert2bert-no-cross-attn-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GItaf/bert2bert-no-cross-attn-decoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GItaf/bert2bert-no-cross-attn-decoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("GItaf/bert2bert-no-cross-attn-decoder") model = AutoModelForCausalLM.from_pretrained("GItaf/bert2bert-no-cross-attn-decoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GItaf/bert2bert-no-cross-attn-decoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GItaf/bert2bert-no-cross-attn-decoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GItaf/bert2bert-no-cross-attn-decoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GItaf/bert2bert-no-cross-attn-decoder
- SGLang
How to use GItaf/bert2bert-no-cross-attn-decoder 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 "GItaf/bert2bert-no-cross-attn-decoder" \ --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": "GItaf/bert2bert-no-cross-attn-decoder", "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 "GItaf/bert2bert-no-cross-attn-decoder" \ --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": "GItaf/bert2bert-no-cross-attn-decoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GItaf/bert2bert-no-cross-attn-decoder with Docker Model Runner:
docker model run hf.co/GItaf/bert2bert-no-cross-attn-decoder
Commit History
-
Update README.md
996ef85 -
Update README.md
d0ce73a -
Upload pytorch_model.bin
188dda9 -
Update README.md
064287e -
Upload tokenizer_config.json
bed8c1d -
Upload tokenizer.json
d64ae85 -
Upload tokenizer.json
e35cf9e -
Upload tokenizer_config.json
96b157f -
Upload README.md
1d85286 -
Upload vocab.txt
00b7d96 -
Upload config.json
ebb125a -
Upload pytorch_model.bin
45b7ed2
-
Upload pytorch_model.bin
0e6726a -
add
BrandonC83107152e48 -
delete
BrandonC8310440e33c
-
Training in progress, epoch 5
e4c8353 -
Training in progress, epoch 4
e06769c -
Training in progress, epoch 3
4528a88 -
Training in progress, epoch 2
a737951 -
Training in progress, epoch 1
eaf44f4 -
initial commit
3c1d119