Text Classification
Transformers
Safetensors
llama
multi-label
question-answering
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use saiteki-kai/QA-Llama-3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saiteki-kai/QA-Llama-3.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="saiteki-kai/QA-Llama-3.1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("saiteki-kai/QA-Llama-3.1") model = AutoModelForSequenceClassification.from_pretrained("saiteki-kai/QA-Llama-3.1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "LlamaForSequenceClassification" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "cls_dropout": 0.1, | |
| "eos_token_id": [ | |
| 128001, | |
| 128008, | |
| 128009 | |
| ], | |
| "finetuning_task": "text-classification", | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "id2label": { | |
| "0": "animal_abuse", | |
| "1": "child_abuse", | |
| "2": "controversial_topics,politics", | |
| "3": "discrimination,stereotype,injustice", | |
| "4": "drug_abuse,weapons,banned_substance", | |
| "5": "financial_crime,property_crime,theft", | |
| "6": "hate_speech,offensive_language", | |
| "7": "misinformation_regarding_ethics,laws_and_safety", | |
| "8": "non_violent_unethical_behavior", | |
| "9": "privacy_violation", | |
| "10": "self_harm", | |
| "11": "sexually_explicit,adult_content", | |
| "12": "terrorism,organized_crime", | |
| "13": "violence,aiding_and_abetting,incitement" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "label2id": { | |
| "animal_abuse": 0, | |
| "child_abuse": 1, | |
| "controversial_topics,politics": 2, | |
| "discrimination,stereotype,injustice": 3, | |
| "drug_abuse,weapons,banned_substance": 4, | |
| "financial_crime,property_crime,theft": 5, | |
| "hate_speech,offensive_language": 6, | |
| "misinformation_regarding_ethics,laws_and_safety": 7, | |
| "non_violent_unethical_behavior": 8, | |
| "privacy_violation": 9, | |
| "self_harm": 10, | |
| "sexually_explicit,adult_content": 11, | |
| "terrorism,organized_crime": 12, | |
| "violence,aiding_and_abetting,incitement": 13 | |
| }, | |
| "max_position_embeddings": 131072, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 128004, | |
| "pretraining_tp": 1, | |
| "problem_type": "multi_label_classification", | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "factor": 8.0, | |
| "high_freq_factor": 4.0, | |
| "low_freq_factor": 1.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_type": "llama3" | |
| }, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.51.3", | |
| "use_cache": true, | |
| "vocab_size": 128256 | |
| } | |