Transformers
ONNX
Safetensors
English
t5
text2text-generation
encoder-decoder
base-model
lora
adapters
ul2
int8
text-generation-inference
Instructions to use KeelCore/KeelCore-750M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KeelCore/KeelCore-750M with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KeelCore/KeelCore-750M") model = AutoModelForSeq2SeqLM.from_pretrained("KeelCore/KeelCore-750M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from KeelCore/KeelCore-750M: direct link, hf CLI and curl.
- Browser
- Download file 287 Bytes
-
https://huggingface.co/KeelCore/KeelCore-750M/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://KeelCore/KeelCore-750M/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/KeelCore/KeelCore-750M/resolve/main/tokenizer_config.json
287 Bytes
| { | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "model_max_length": 2048, | |
| "pad_token": "<pad>", | |
| "eos_token": "</s>", | |
| "unk_token": "<unk>", | |
| "clean_up_tokenization_spaces": false, | |
| "add_prefix_space": false, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ] | |
| } |