Translation
Transformers
PyTorch
TensorBoard
Safetensors
English
marian
text2text-generation
Generated from Trainer
Instructions to use SRDdev/HingFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/HingFlow with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="SRDdev/HingFlow")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SRDdev/HingFlow") model = AutoModelForSeq2SeqLM.from_pretrained("SRDdev/HingFlow", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from SRDdev/HingFlow: direct link, hf CLI and curl.
- Browser
- Download file 282 Bytes
-
https://huggingface.co/SRDdev/HingFlow/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://SRDdev/HingFlow/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/SRDdev/HingFlow/resolve/main/tokenizer_config.json
282 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "</s>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "separate_vocabs": false, | |
| "source_lang": "eng", | |
| "sp_model_kwargs": {}, | |
| "target_lang": "hin", | |
| "tokenizer_class": "MarianTokenizer", | |
| "unk_token": "<unk>" | |
| } | |