Instructions to use deepaknh/falcon7b-FineTuningQLORA_IncrementTrainingVersion2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use deepaknh/falcon7b-FineTuningQLORA_IncrementTrainingVersion2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ybelkada/falcon-7b-sharded-bf16") model = PeftModel.from_pretrained(base_model, "deepaknh/falcon7b-FineTuningQLORA_IncrementTrainingVersion2") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from deepaknh/falcon7b-FineTuningQLORA_IncrementTrainingVersion2: direct link, hf CLI and curl.
- Browser
- Download file 180 Bytes
-
https://huggingface.co/deepaknh/falcon7b-FineTuningQLORA_IncrementTrainingVersion2/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://deepaknh/falcon7b-FineTuningQLORA_IncrementTrainingVersion2/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/deepaknh/falcon7b-FineTuningQLORA_IncrementTrainingVersion2/resolve/main/tokenizer_config.json
180 Bytes
| { | |
| "add_prefix_space": false, | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 2048, | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |