Instructions to use Aybars/XLM_Turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aybars/XLM_Turkish with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" 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("question-answering", model="Aybars/XLM_Turkish")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Aybars/XLM_Turkish") model = AutoModelForQuestionAnswering.from_pretrained("Aybars/XLM_Turkish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Aybars/XLM_Turkish: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/Aybars/XLM_Turkish/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Aybars/XLM_Turkish/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aybars/XLM_Turkish/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 2b7a65d794fa7056b0624c6966ae42668f3bbc7e97f9f1851276fe8f0db4ec87
- Size of remote file:
- 1.11 GB
- SHA256:
- 84ba417110bac3998d0bb994bcbd70541a1ce4dd3bf0332faabf9c8300df03b0
路
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