Feature Extraction
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use binh230/finetune_bge_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binh230/finetune_bge_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="binh230/finetune_bge_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("binh230/finetune_bge_test") model = AutoModel.from_pretrained("binh230/finetune_bge_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from binh230/finetune_bge_test: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/binh230/finetune_bge_test/resolve/main/tokenizer.json
- Command line
-
hf download hf://binh230/finetune_bge_test/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/binh230/finetune_bge_test/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- cfb5640e76bbfb7e6c07beec307a86ef1e893b51d7cbceacc91ec7f998f06610
- Size of remote file:
- 17.1 MB
- SHA256:
- 8bf8afbfd11306bd872018c53bfdf2e160a56f8edbcf49933324404791c148d3
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