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 13
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 898314360
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:502ada92a7e999314797cb3c1626d56bed0230526b2c36967c584bb968421518
|
| 3 |
size 898314360
|
runs/Apr09_09-43-22_fedora/events.out.tfevents.1712627004.fedora.1475234.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f5c52793ca4be3b47374605bbd33eeefe3a8eabf3c27188a85f00effb5f1dd23
|
| 3 |
+
size 89315
|