Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use erickdp/comprehendo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erickdp/comprehendo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erickdp/comprehendo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erickdp/comprehendo") model = AutoModelForSequenceClassification.from_pretrained("erickdp/comprehendo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from erickdp/comprehendo: direct link, hf CLI and curl.
- Browser
- Download file 23 Bytes
-
https://huggingface.co/erickdp/comprehendo/resolve/main/added_tokens.json
- Command line
-
hf download hf://erickdp/comprehendo/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/erickdp/comprehendo/resolve/main/added_tokens.json
23 Bytes
| { | |
| "[MASK]": 128000 | |
| } | |