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Mixtral-tiny-GPTQ

Text Generation
Transformers
Safetensors
mixtral
text-generation-inference
4-bit precision
gptq
Model card Files Community
Mixtral-tiny-GPTQ
File size: 2,210 Bytes 
3901bec
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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{
    "_name_or_path": "/workspace/process/hf-internal-testing_mixtral-tiny/source",
    "architectures": [
        "MixtralForCausalLM"
    ],
    "attention_dropout": 0.0,
    "bos_token_id": 1,
    "eos_token_id": 2,
    "hidden_act": "silu",
    "hidden_size": 1024,
    "initializer_range": 0.02,
    "intermediate_size": 3584,
    "max_position_embeddings": 131072,
    "model_type": "mixtral",
    "num_attention_heads": 32,
    "num_experts_per_tok": 2,
    "num_hidden_layers": 2,
    "num_key_value_heads": 8,
    "num_local_experts": 8,
    "output_router_logits": false,
    "pad_token_id": 0,
    "pretraining_tp": 1,
    "rms_norm_eps": 1e-05,
    "rope_theta": 10000.0,
    "router_aux_loss_coef": 0.001,
    "sliding_window": 4096,
    "tie_word_embeddings": false,
    "torch_dtype": "float16",
    "transformers_version": "4.36.0.dev0",
    "use_cache": true,
    "vocab_size": 32000,
    "quantization_config": {
        "bits": 4,
        "group_size": 128,
        "damp_percent": 0.1,
        "desc_act": true,
        "sym": true,
        "true_sequential": true,
        "model_name_or_path": null,
        "model_file_base_name": "model",
        "inside_layer_modules" : [
        ["self_attn.k_proj", "self_attn.v_proj", "self_attn.q_proj"],
        ["self_attn.o_proj"],
        ["block_sparse_moe.experts.0.w1", "block_sparse_moe.experts.0.w2", "block_sparse_moe.experts.0.w3"],
        ["block_sparse_moe.experts.1.w1", "block_sparse_moe.experts.1.w2", "block_sparse_moe.experts.1.w3"],
        ["block_sparse_moe.experts.2.w1", "block_sparse_moe.experts.2.w2", "block_sparse_moe.experts.2.w3"],
        ["block_sparse_moe.experts.3.w1", "block_sparse_moe.experts.3.w2", "block_sparse_moe.experts.3.w3"],
        ["block_sparse_moe.experts.4.w1", "block_sparse_moe.experts.4.w2", "block_sparse_moe.experts.4.w3"],
        ["block_sparse_moe.experts.5.w1", "block_sparse_moe.experts.5.w2", "block_sparse_moe.experts.5.w3"],
        ["block_sparse_moe.experts.6.w1", "block_sparse_moe.experts.6.w2", "block_sparse_moe.experts.6.w3"],
        ["block_sparse_moe.experts.7.w1", "block_sparse_moe.experts.7.w2", "block_sparse_moe.experts.7.w3"]],
        "quant_method": "gptq"
    }
}