Text Classification
Transformers
Safetensors
Hindi
English
bert
hinglish
code-mixed
research
hate-speech-detection
text-embeddings-inference
Instructions to use OmTheLast/muril-hinglish-mixed-cm-thar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OmTheLast/muril-hinglish-mixed-cm-thar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OmTheLast/muril-hinglish-mixed-cm-thar")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OmTheLast/muril-hinglish-mixed-cm-thar") model = AutoModelForSequenceClassification.from_pretrained("OmTheLast/muril-hinglish-mixed-cm-thar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_metrics.json from OmTheLast/muril-hinglish-mixed-cm-thar: direct link, hf CLI and curl.
- Browser
- Download file 386 Bytes
-
https://huggingface.co/OmTheLast/muril-hinglish-mixed-cm-thar/resolve/main/eval_metrics.json
- Command line
-
hf download hf://OmTheLast/muril-hinglish-mixed-cm-thar/eval_metrics.json
-
curl -L -o eval_metrics.json https://huggingface.co/OmTheLast/muril-hinglish-mixed-cm-thar/resolve/main/eval_metrics.json
386 Bytes
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.5548564687377113, | |
| "eval_f1_hate": 0.0, | |
| "eval_f1_macro": 0.35685381891755186, | |
| "eval_loss": 0.6871203780174255, | |
| "eval_precision_hate": 0.0, | |
| "eval_precision_macro": 0.27742823436885566, | |
| "eval_recall_hate": 0.0, | |
| "eval_recall_macro": 0.5, | |
| "eval_runtime": 6.7265, | |
| "eval_samples_per_second": 378.059, | |
| "eval_steps_per_second": 47.276 | |
| } |