Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use roscazo/vih_explainability with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roscazo/vih_explainability with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="roscazo/vih_explainability")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("roscazo/vih_explainability") model = AutoModelForSequenceClassification.from_pretrained("roscazo/vih_explainability", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from roscazo/vih_explainability: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/roscazo/vih_explainability/resolve/main/training_args.bin
- Command line
-
hf download hf://roscazo/vih_explainability/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/roscazo/vih_explainability/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 00f2587afac7049724c55e52c4f4ac316212577685d8b8300c6c45ff18f19e20
- Size of remote file:
- 5.11 kB
- SHA256:
- 6cf3dde74bd486074cc558d67a153bcc9410fb75e4de2ebb90ad42b3a86c55d5
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