Instructions to use jvonrad/OLMo-2-7B-CPT-SFT-10k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jvonrad/OLMo-2-7B-CPT-SFT-10k with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jvonrad/olmo-2-7b-finetranslations") model = PeftModel.from_pretrained(base_model, "jvonrad/OLMo-2-7B-CPT-SFT-10k") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from jvonrad/OLMo-2-7B-CPT-SFT-10k: direct link, hf CLI and curl.
- Browser
- Download file 369 Bytes
-
https://huggingface.co/jvonrad/OLMo-2-7B-CPT-SFT-10k/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://jvonrad/OLMo-2-7B-CPT-SFT-10k/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/jvonrad/OLMo-2-7B-CPT-SFT-10k/resolve/main/tokenizer_config.json
369 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|pad|>", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<|endoftext|>" | |
| } | |