Instructions to use httpschiara/trocr-base-handwritten-modconfig with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use httpschiara/trocr-base-handwritten-modconfig with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="httpschiara/trocr-base-handwritten-modconfig")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("httpschiara/trocr-base-handwritten-modconfig") model = AutoModelForImageTextToText.from_pretrained("httpschiara/trocr-base-handwritten-modconfig") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use httpschiara/trocr-base-handwritten-modconfig with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "httpschiara/trocr-base-handwritten-modconfig" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "httpschiara/trocr-base-handwritten-modconfig", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/httpschiara/trocr-base-handwritten-modconfig
- SGLang
How to use httpschiara/trocr-base-handwritten-modconfig 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 "httpschiara/trocr-base-handwritten-modconfig" \ --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": "httpschiara/trocr-base-handwritten-modconfig", "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 "httpschiara/trocr-base-handwritten-modconfig" \ --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": "httpschiara/trocr-base-handwritten-modconfig", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use httpschiara/trocr-base-handwritten-modconfig with Docker Model Runner:
docker model run hf.co/httpschiara/trocr-base-handwritten-modconfig
Upload model
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1335747032
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1e323906948bc07d57bb66083aad18c146f3de5dacf6f698684ba36363566879
|
| 3 |
size 1335747032
|