Instructions to use tencent/Hy-MT2-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/Hy-MT2-7B 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="tencent/Hy-MT2-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tencent/Hy-MT2-7B") model = AutoModelForCausalLM.from_pretrained("tencent/Hy-MT2-7B") - Notebooks
- Google Colab
- Kaggle
| { | |
| "fp16": { | |
| "enabled": "auto", | |
| "loss_scale": 0, | |
| "loss_scale_window": 1000, | |
| "initial_scale_power": 16, | |
| "hysteresis": 2, | |
| "min_loss_scale": 1 | |
| }, | |
| "bf16": { | |
| "enabled": "auto" | |
| }, | |
| "zero_optimization": { | |
| "stage": 3, | |
| "offload_optimizer": { | |
| "device": "cpu", | |
| "pin_memory": true | |
| }, | |
| "offload_param": { | |
| "device": "cpu", | |
| "pin_memory": true | |
| }, | |
| "overlap_comm": true, | |
| "contiguous_gradients": true, | |
| "sub_group_size": 1e9, | |
| "reduce_bucket_size": "auto", | |
| "stage3_prefetch_bucket_size": "auto", | |
| "stage3_param_persistence_threshold": "auto", | |
| "stage3_max_live_parameters": 1e9, | |
| "stage3_max_reuse_distance": 1e9, | |
| "stage3_gather_16bit_weights_on_model_save": false | |
| }, | |
| "gradient_accumulation_steps": "auto", | |
| "gradient_clipping": "auto", | |
| "steps_per_print": 10, | |
| "train_batch_size": "auto", | |
| "train_micro_batch_size_per_gpu": "auto", | |
| "wall_clock_breakdown": false | |
| } |