Instructions to use hf-internal-testing/tiny-random-XLMModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XLMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-XLMModel")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XLMModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-XLMModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6afb41aa1e801c9f1f2e5e67d10f6523ddcfcd6b15d969b03c7e38dd566911a
- Size of remote file:
- 4.28 MB
- SHA256:
- 40e258ad6b3e26c74681f114c53b7b003bf9c7806eee463ec853b5b7addc4d16
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