Instructions to use tahrirchi/dilmash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tahrirchi/dilmash 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="tahrirchi/dilmash")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tahrirchi/dilmash") model = AutoModelForSeq2SeqLM.from_pretrained("tahrirchi/dilmash", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05d7951c06d692396a73459ec867bacca73a25de3fef2c03ca2838194a3b67bb
- Size of remote file:
- 2.51 GB
- SHA256:
- 9e120e9464252d23f96cce11ba61bfc67188c4060ae7b6cb47b98c5a4adf0055
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