Feature Extraction
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use comet24082002/finetuned_bge_ver7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use comet24082002/finetuned_bge_ver7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="comet24082002/finetuned_bge_ver7")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("comet24082002/finetuned_bge_ver7") model = AutoModel.from_pretrained("comet24082002/finetuned_bge_ver7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from comet24082002/finetuned_bge_ver7: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/comet24082002/finetuned_bge_ver7/resolve/main/training_args.bin
- Command line
-
hf download hf://comet24082002/finetuned_bge_ver7/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/comet24082002/finetuned_bge_ver7/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 616f9574d31b9eb46ef94944721c76b5f667f0e1b74cab448acab542d6591017
- Size of remote file:
- 5.24 kB
- SHA256:
- f479f8c8a6f495a9676c61f62f96006a16f3b636168e636bc72237314c05bb59
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