Translation
Transformers
Safetensors
Pnar
English
m2m_100
text2text-generation
machine-translation
pnar
english
low-resource
nllb
northeast-india
austroasiatic
khasian
mwirelabs
Eval Results (legacy)
Instructions to use MWirelabs/pnar-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MWirelabs/pnar-mt 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="MWirelabs/pnar-mt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MWirelabs/pnar-mt") model = AutoModelForSeq2SeqLM.from_pretrained("MWirelabs/pnar-mt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MWirelabs/pnar-mt: direct link, hf CLI and curl.
- Browser
- Download file 17.3 MB
-
https://huggingface.co/MWirelabs/pnar-mt/resolve/main/tokenizer.json
- Command line
-
hf download hf://MWirelabs/pnar-mt/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MWirelabs/pnar-mt/resolve/main/tokenizer.json
17.3 MB
- Xet hash:
- 33909d54744243a65726b333c6f3ff41329e6e804ccc66c746625e1f4084d7c8
- Size of remote file:
- 17.3 MB
- SHA256:
- 5a2bb2ebc36fbeb10034aaf90ba91a85179a09da69ef9605c2c63f1c591195ed
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