Instructions to use Lipdog/Qwen3-Reranker-4B-mlx-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lipdog/Qwen3-Reranker-4B-mlx-fp16 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Lipdog/Qwen3-Reranker-4B-mlx-fp16") model = AutoModelForCausalLM.from_pretrained("Lipdog/Qwen3-Reranker-4B-mlx-fp16") - MLX
How to use Lipdog/Qwen3-Reranker-4B-mlx-fp16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3-Reranker-4B-mlx-fp16 Lipdog/Qwen3-Reranker-4B-mlx-fp16
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
File size: 784 Bytes
42a8bea | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | {
"architectures": [
"Qwen3ForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 151643,
"eos_token_id": 151645,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 2560,
"initializer_range": 0.02,
"intermediate_size": 9728,
"max_position_embeddings": 40960,
"max_window_layers": 36,
"model_type": "qwen3",
"num_attention_heads": 32,
"num_hidden_layers": 36,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 1000000,
"sliding_window": null,
"tie_word_embeddings": true,
"torch_dtype": "bfloat16",
"transformers_version": "4.51.3",
"use_cache": true,
"use_sliding_window": false,
"vocab_size": 151669
} |