Instructions to use EndLessTime/fine_tuned_per_domain_balanced_32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EndLessTime/fine_tuned_per_domain_balanced_32B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EndLessTime/fine_tuned_per_domain_balanced_32B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EndLessTime/fine_tuned_per_domain_balanced_32B") model = AutoModelForSequenceClassification.from_pretrained("EndLessTime/fine_tuned_per_domain_balanced_32B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "Qwen/Qwen1.5-32B", | |
| "architectures": [ | |
| "Qwen2ForSequenceClassification" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 151643, | |
| "eos_token_id": 151643, | |
| "hidden_act": "silu", | |
| "hidden_size": 5120, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 27392, | |
| "max_position_embeddings": 32768, | |
| "max_window_layers": 35, | |
| "model_type": "qwen2", | |
| "num_attention_heads": 40, | |
| "num_hidden_layers": 64, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 151643, | |
| "problem_type": "single_label_classification", | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 1000000.0, | |
| "sliding_window": 32768, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.49.0", | |
| "use_cache": true, | |
| "use_sliding_window": false, | |
| "vocab_size": 152064 | |
| } | |