Instructions to use jvelja/BERT_vllm-gemma2b-deterministic_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jvelja/BERT_vllm-gemma2b-deterministic_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jvelja/BERT_vllm-gemma2b-deterministic_7")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jvelja/BERT_vllm-gemma2b-deterministic_7") model = AutoModelForSequenceClassification.from_pretrained("jvelja/BERT_vllm-gemma2b-deterministic_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jvelja/BERT_vllm-gemma2b-deterministic_7: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/jvelja/BERT_vllm-gemma2b-deterministic_7/resolve/main/tokenizer.json
- Command line
-
hf download hf://jvelja/BERT_vllm-gemma2b-deterministic_7/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/jvelja/BERT_vllm-gemma2b-deterministic_7/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.