Translation
Transformers
Safetensors
English
Thai
qwen3_5
image-text-to-text
thai
english
instruction-following
machine-translation
Instructions to use iapp/ChindaMT-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iapp/ChindaMT-4B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="iapp/ChindaMT-4B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("iapp/ChindaMT-4B") model = AutoModelForMultimodalLM.from_pretrained("iapp/ChindaMT-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from iapp/ChindaMT-4B: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/iapp/ChindaMT-4B/resolve/main/tokenizer.json
- Command line
-
hf download hf://iapp/ChindaMT-4B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/iapp/ChindaMT-4B/resolve/main/tokenizer.json
20 MB
- Xet hash:
- 458bcbf483ed805b4297af928f717e64bd00c633a07be5fae5717cacbd48e2ef
- Size of remote file:
- 20 MB
- SHA256:
- 87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4
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