Instructions to use daviBera/intern35_2b_lora_expert_chart-102400 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daviBera/intern35_2b_lora_expert_chart-102400 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("../checkpoints/base_models/InternVL3_5-2B-Pretrained-HF") model = PeftModel.from_pretrained(base_model, "daviBera/intern35_2b_lora_expert_chart-102400") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from daviBera/intern35_2b_lora_expert_chart-102400: direct link, hf CLI and curl.
- Browser
- Download file 72 Bytes
-
https://huggingface.co/daviBera/intern35_2b_lora_expert_chart-102400/resolve/main/processor_config.json
- Command line
-
hf download hf://daviBera/intern35_2b_lora_expert_chart-102400/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/daviBera/intern35_2b_lora_expert_chart-102400/resolve/main/processor_config.json
72 Bytes
| { | |
| "image_seq_length": 256, | |
| "processor_class": "InternVLProcessor" | |
| } | |