Feature Extraction
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use comet24082002/finetuned_bge_ver21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use comet24082002/finetuned_bge_ver21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="comet24082002/finetuned_bge_ver21")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("comet24082002/finetuned_bge_ver21") model = AutoModel.from_pretrained("comet24082002/finetuned_bge_ver21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from comet24082002/finetuned_bge_ver21: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/comet24082002/finetuned_bge_ver21/resolve/main/tokenizer.json
- Command line
-
hf download hf://comet24082002/finetuned_bge_ver21/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/comet24082002/finetuned_bge_ver21/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 6c04a13e5301748639a0aff20dafcf438c1592eb3be82922c20828a946fdc6ef
- Size of remote file:
- 17.1 MB
- SHA256:
- c564888dbafbfebcc7a62d2f4049afe83e6fb5acd50a97082a84407c77ddd8ff
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