Instructions to use hadidev/Vit_roberta_urdu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadidev/Vit_roberta_urdu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="hadidev/Vit_roberta_urdu")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("hadidev/Vit_roberta_urdu") model = AutoModelForImageTextToText.from_pretrained("hadidev/Vit_roberta_urdu") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use hadidev/Vit_roberta_urdu with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hadidev/Vit_roberta_urdu" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hadidev/Vit_roberta_urdu", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hadidev/Vit_roberta_urdu
- SGLang
How to use hadidev/Vit_roberta_urdu 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 "hadidev/Vit_roberta_urdu" \ --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": "hadidev/Vit_roberta_urdu", "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 "hadidev/Vit_roberta_urdu" \ --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": "hadidev/Vit_roberta_urdu", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hadidev/Vit_roberta_urdu with Docker Model Runner:
docker model run hf.co/hadidev/Vit_roberta_urdu
Training in progress, epoch 4
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 963335467
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ee66e8eff904766deb3bcb8246ed063c4d26c544f0817f6199db0f7d36e079d6
|
| 3 |
size 963335467
|
runs/Jul29_21-29-31_52ee3afcb014/events.out.tfevents.1659130178.52ee3afcb014.33.0
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:b0f4f8c6eff78ab13d03e9ce7c8a66084329ffb7b26121832029ab54488f297c
|
| 3 |
+
size 81900
|