Instructions to use brownyeyez/InternVL3_5-Rerank with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brownyeyez/InternVL3_5-Rerank with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="brownyeyez/InternVL3_5-Rerank", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("brownyeyez/InternVL3_5-Rerank", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from brownyeyez/InternVL3_5-Rerank: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/brownyeyez/InternVL3_5-Rerank/resolve/main/tokenizer.json
- Command line
-
hf download hf://brownyeyez/InternVL3_5-Rerank/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/brownyeyez/InternVL3_5-Rerank/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 9a632633b0d91f15eb5a649e3484c9d60e77eea5380273468f0b310a9947965f
- Size of remote file:
- 11.4 MB
- SHA256:
- 6581c44164d273d4222df982905a7e0450dcf3a4a7ebe98f9ec53e4de05beffe
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