Translation
Transformers
Safetensors
Kannada
English
controlmt
text2text-generation
machine-translation
kannada
english
indic
low-resource
code-mix
encoder-decoder
custom_code
Eval Results (legacy)
Instructions to use anandkaman/controlmt-v2.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anandkaman/controlmt-v2.3 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="anandkaman/controlmt-v2.3", trust_remote_code=True)# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("anandkaman/controlmt-v2.3", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Fix HF auto_map (add tokenizer_config.json + list form); honest style framing + add curated eval scores
37b4c07 verified | { | |
| "tokenizer_class": "ControlMTTokenizer", | |
| "auto_map": { | |
| "AutoTokenizer": ["tokenization_controlmt.ControlMTTokenizer", null] | |
| }, | |
| "model_max_length": 320, | |
| "bos_token": "<s>", | |
| "eos_token": "</s>", | |
| "unk_token": "<unk>", | |
| "pad_token": "<pad>", | |
| "clean_up_tokenization_spaces": false, | |
| "use_fast": false | |
| } | |