Image-Text-to-Text
PEFT
Safetensors
lora
llama-factory
coral-reef
biodiversity
fine-grained-classification
reefnet
conversational
Instructions to use ReefNet/reefnet-internvl3.5-8b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ReefNet/reefnet-internvl3.5-8b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenGVLab/InternVL3_5-8B-HF") model = PeftModel.from_pretrained(base_model, "ReefNet/reefnet-internvl3.5-8b-lora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ReefNet/reefnet-internvl3.5-8b-lora: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/ReefNet/reefnet-internvl3.5-8b-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://ReefNet/reefnet-internvl3.5-8b-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ReefNet/reefnet-internvl3.5-8b-lora/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 17627d3b1b74ac1fdcb7341bd50d1638a9d66797e85a06d71d4ad8ada0f5d639
- Size of remote file:
- 11.4 MB
- SHA256:
- 7b9d18660f656ae5a87df2d5d6ed990e80f292d3473c1a35cae8259a5d28cd67
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