Image-Text-to-Text
Transformers
TensorBoard
Safetensors
vision-encoder-decoder
Generated from Trainer
Instructions to use ChayanM/ViT-Bert_Mimic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChayanM/ViT-Bert_Mimic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ChayanM/ViT-Bert_Mimic")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("ChayanM/ViT-Bert_Mimic") model = AutoModelForImageTextToText.from_pretrained("ChayanM/ViT-Bert_Mimic") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ChayanM/ViT-Bert_Mimic with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ChayanM/ViT-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/ViT-Bert_Mimic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ChayanM/ViT-Bert_Mimic
- SGLang
How to use ChayanM/ViT-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/ViT-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/ViT-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/ViT-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/ViT-Bert_Mimic", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ChayanM/ViT-Bert_Mimic with Docker Model Runner:
docker model run hf.co/ChayanM/ViT-Bert_Mimic
Training in progress, epoch 1
Browse files- config.json +0 -1
- model.safetensors +1 -1
- training_args.bin +1 -1
config.json
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"eos_token_id": 102,
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"is_encoder_decoder": true,
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"max_length": 200,
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"model_type": "vision-encoder-decoder",
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"tie_word_embeddings": false,
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"eos_token_id": 102,
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"is_encoder_decoder": true,
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"model_type": "vision-encoder-decoder",
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"tie_word_embeddings": false,
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model.safetensors
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training_args.bin
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