Text Classification
Transformers
Safetensors
German
llama
feature-extraction
reranker
cross-encoder
german
retrieval
rag
on-prem
text-embeddings-inference
Instructions to use keyvan-ai/Mankei-326M-Reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keyvan-ai/Mankei-326M-Reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keyvan-ai/Mankei-326M-Reranker")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("keyvan-ai/Mankei-326M-Reranker") model = AutoModel.from_pretrained("keyvan-ai/Mankei-326M-Reranker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "LlamaModel" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 0, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 1, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 960, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 2560, | |
| "max_position_embeddings": 2048, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 15, | |
| "num_hidden_layers": 30, | |
| "num_key_value_heads": 5, | |
| "pad_token_id": 1, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_parameters": { | |
| "rope_theta": 100000.0, | |
| "rope_type": "default" | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.15.0", | |
| "use_cache": false, | |
| "vocab_size": 32768 | |
| } | |