Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use franfj/DIPROMATS_subtask_1_base_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_1_base_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_1_base_train")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_1_base_train") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_1_base_train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from franfj/DIPROMATS_subtask_1_base_train: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/franfj/DIPROMATS_subtask_1_base_train/resolve/main/model.safetensors
- Command line
-
hf download hf://franfj/DIPROMATS_subtask_1_base_train/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/franfj/DIPROMATS_subtask_1_base_train/resolve/main/model.safetensors
1.11 GB
- Xet hash:
- 1ff591c767c1ee8802a4343f8f4fb1699a156f6fb9c747bc9b7a66eedb09a6bb
- Size of remote file:
- 1.11 GB
- SHA256:
- 2a92ca9b975d8552a1eb4b8d369ee012183c348d25c7647dbeebba513a0247c6
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