Text Generation
PEFT
Safetensors
information-extraction
json
structured-outputs
qwen
lora
conversational
Instructions to use Adityapande403/universal-json-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Adityapande403/universal-json-extractor with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "Adityapande403/universal-json-extractor") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Adityapande403/universal-json-extractor: direct link, hf CLI and curl.
- Browser
- Download file 724 Bytes
-
https://huggingface.co/Adityapande403/universal-json-extractor/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Adityapande403/universal-json-extractor/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Adityapande403/universal-json-extractor/resolve/main/tokenizer_config.json
724 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<|object_ref_start|>", | |
| "<|object_ref_end|>", | |
| "<|box_start|>", | |
| "<|box_end|>", | |
| "<|quad_start|>", | |
| "<|quad_end|>", | |
| "<|vision_start|>", | |
| "<|vision_end|>", | |
| "<|vision_pad|>", | |
| "<|image_pad|>", | |
| "<|video_pad|>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 131072, | |
| "pad_token": "<|endoftext|>", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |