opt-125m-gptq-4bit / config.json
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{
"_name_or_path": "facebook/opt-125m",
"_remove_final_layer_norm": false,
"activation_dropout": 0.0,
"activation_function": "relu",
"architectures": [
"OPTForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 2,
"do_layer_norm_before": true,
"dropout": 0.1,
"enable_bias": true,
"eos_token_id": 2,
"ffn_dim": 3072,
"hidden_size": 768,
"init_std": 0.02,
"layer_norm_elementwise_affine": true,
"layerdrop": 0.0,
"max_position_embeddings": 2048,
"model_type": "opt",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 1,
"prefix": "</s>",
"quantization_config": {
"batch_size": 1,
"bits": 4,
"block_name_to_quantize": "model.decoder.layers",
"damp_percent": 0.1,
"dataset": [
"auto-gptq is an easy-to-use model quantization library with user-friendly apis, based on GPTQ algorithm."
],
"desc_act": false,
"disable_exllama": false,
"group_size": 128,
"model_seqlen": 2048,
"module_name_preceding_first_block": [
"model.decoder.embed_tokens",
"model.decoder.embed_positions",
"model.decoder.final_layer_norm"
],
"pad_token_id": null,
"quant_method": "gptq",
"sym": true,
"tokenizer": null,
"true_sequential": true,
"use_cuda_fp16": true
},
"torch_dtype": "float16",
"transformers_version": "4.32.1",
"use_cache": true,
"vocab_size": 50272,
"word_embed_proj_dim": 768
}