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")# 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
Download tokenizer.json from proxy3d/multi-motions-28: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/proxy3d/multi-motions-28/resolve/main/tokenizer.json
- Command line
-
hf download hf://proxy3d/multi-motions-28/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/proxy3d/multi-motions-28/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 0436e59ec8a6df660e715844776703b9d9a44063ac6917514ee22777c794fbb2
- Size of remote file:
- 17.1 MB
- SHA256:
- ea09a711f7adcb7e3bc41b614e59b829fc98e7b50b94d273d029315524364069
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