Instructions to use hf-tiny-model-private/tiny-random-XLMForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-XLMForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-XLMForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XLMForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-XLMForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from hf-tiny-model-private/tiny-random-XLMForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 4.28 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-XLMForTokenClassification/resolve/refs%2Fpr%2F1/tf_model.h5
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-XLMForTokenClassification@refs/pr/1/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/hf-tiny-model-private/tiny-random-XLMForTokenClassification/resolve/refs%2Fpr%2F1/tf_model.h5
4.28 MB
- Xet hash:
- 5092ab33453a2d1f3e4727a623df2a8e5f348d011578aef40f4d772156dd6d94
- Size of remote file:
- 4.28 MB
- SHA256:
- efe8fc22e9a2937184ef5acf94b8cb3fd53275d4adf508df7a3886516f493519
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