Instructions to use ChayanM/Swin-Bert_Mimic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChayanM/Swin-Bert_Mimic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ChayanM/Swin-Bert_Mimic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("ChayanM/Swin-Bert_Mimic") model = AutoModelForMultimodalLM.from_pretrained("ChayanM/Swin-Bert_Mimic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ChayanM/Swin-Bert_Mimic with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ChayanM/Swin-Bert_Mimic" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ChayanM/Swin-Bert_Mimic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ChayanM/Swin-Bert_Mimic
- SGLang
How to use ChayanM/Swin-Bert_Mimic 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 "ChayanM/Swin-Bert_Mimic" \ --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": "ChayanM/Swin-Bert_Mimic", "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 "ChayanM/Swin-Bert_Mimic" \ --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": "ChayanM/Swin-Bert_Mimic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ChayanM/Swin-Bert_Mimic with Docker Model Runner:
docker model run hf.co/ChayanM/Swin-Bert_Mimic
Commit History
-
Model save
Verified signaturecc9c02f -
Training in progress, epoch 20
Verified signature330b14f -
Training in progress, epoch 19
Verified signature419583d -
Training in progress, epoch 18
Verified signaturee0afc9a -
Training in progress, epoch 17
Verified signaturebfd7b49 -
Training in progress, epoch 16
Verified signaturea8749b0 -
Training in progress, epoch 15
Verified signaturec2b1358 -
Training in progress, epoch 14
Verified signature8df00b6
-
Training in progress, epoch 13
Verified signature528a681 -
Training in progress, epoch 12
Verified signature4b08d0d -
Training in progress, epoch 11
Verified signatureacb9092 -
Training in progress, epoch 10
Verified signature11462ae -
Training in progress, epoch 9
Verified signature4ca3074 -
Training in progress, epoch 8
Verified signature2dc7867 -
Training in progress, epoch 6
Verified signature0ee157b -
Training in progress, epoch 5
Verified signature188d91a -
Training in progress, epoch 4
Verified signature2c2d4da -
Training in progress, epoch 3
Verified signature1ae12ac
-
Training in progress, epoch 2
Verified signaturedf6f7cd -
Training in progress, epoch 1
Verified signature48284ca -
initial commit
Verified signature463efc5