Text Classification
Transformers
Safetensors
English
Russian
xlm-roberta
emotion-classification
multi-label-classification
goemotions
english
russian
affective-computing
text-embeddings-inference
Instructions to use proxy3d/multi-motions-28 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use proxy3d/multi-motions-28 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="proxy3d/multi-motions-28")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("proxy3d/multi-motions-28") model = AutoModelForSequenceClassification.from_pretrained("proxy3d/multi-motions-28", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
299bfda | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:ea09a711f7adcb7e3bc41b614e59b829fc98e7b50b94d273d029315524364069
size 17082831
|