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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- finetuned |
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- multimodal |
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base_model: mistralai/Mixtral-8x7B-Instruct-v0.1 |
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dataset: ./out |
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inference: false |
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--- |
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These are weights for a version of `mistralai/Mixtral-8x7B-Instruct-v0.1` finetuned for multimodal applications. |
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### Modalities |
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* CLIPVisionModality (use `<image>` in text and provide `images`, encoded as 576 tokens) |
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### Usage |
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GitHub: https://github.com/sshh12/multi_token (includes training scripts and basic inference server) |
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### Dataset |
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./out (558128 examples) |
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``` |
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{'id': '004539375', 'images': ['/data/llava_pretrain_data/images/00453/004539375.jpg'], 'messages': [{'content': 'Render a clear and concise summary of the photo.\n<image>', 'role': 'user'}, {'content': 'select luxury furniture 3 - inch gel memory foam mattress topper', 'role': 'assistant'}]} |
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``` |
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### Training Device(s) |
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``` |
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name, pci.bus_id, vbios_version |
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NVIDIA GeForce RTX 3090, 00000000:B3:00.0, 94.02.42.00.B4 |
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``` |
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### Model |
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``` |
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MistralLMMForCausalLM.model = |
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PeftModelForCausalLM( |
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(base_model): LoraModel( |
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(model): MistralLMMForCausalLM( |
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(model): MistralLMMModel( |
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(embed_tokens): Embedding(32000, 4096) |
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(layers): ModuleList( |
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(0-31): 32 x MistralDecoderLayer( |
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(self_attn): MistralAttention( |
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(q_proj): lora.Linear( |
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(base_layer): Linear(in_features=4096, out_features=4096, bias=False) |
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(lora_dropout): ModuleDict( |
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(default): Dropout(p=0.05, inplace=False) |
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) |
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(lora_A): ModuleDict( |
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(default): Linear(in_features=4096, out_features=64, bias=False) |
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) |
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(lora_B): ModuleDict( |
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(default): Linear(in_features=64, out_features=4096, bias=False) |
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) |
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(lora_embedding_A): ParameterDict() |
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(lora_embedding_B): ParameterDict() |
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) |
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(k_proj): lora.Linear( |
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(base_layer): Linear(in_features=4096, out_features=1024, bias=False) |
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(lora_dropout): ModuleDict( |
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(default): Dropout(p=0.05, inplace=False) |
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) |
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(lora_A): ModuleDict( |
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(default): Linear(in_features=4096, out_features=64, bias=False) |
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) |
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(lora_B): ModuleDict( |
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(default): Linear(in_features=64, out_features=1024, bias=False) |
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) |
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(lora_embedding_A): ParameterDict() |
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(lora_embedding_B): ParameterDict() |
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) |
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(v_proj): lora.Linear( |
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(base_layer): Linear(in_features=4096, out_features=1024, bias=False) |
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(lora_dropout): ModuleDict( |
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(default): Dropout(p=0.05, inplace=False) |
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) |
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(lora_A): ModuleDict( |
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(default): Linear(in_features=4096, out_features=64, bias=False) |
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) |
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(lora_B): ModuleDict( |
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(default): Linear(in_features=64, out_features=1024, bias=False) |
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) |
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(lora_embedding_A): ParameterDict() |
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(lora_embedding_B): ParameterDict() |
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) |
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(o_proj): lora.Linear( |
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(base_layer): Linear(in_features=4096, out_features=4096, bias=False) |
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(lora_dropout): ModuleDict( |
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(default): Dropout(p=0.05, inplace=False) |
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) |
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(lora_A): ModuleDict( |
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(default): Linear(in_features=4096, out_features=64, bias=False) |
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) |
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(lora_B): ModuleDict( |
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(default): Linear(in_features=64, out_features=4096, bias=False) |
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) |
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(lora_embedding_A): ParameterDict() |
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(lora_embedding_B): ParameterDict() |
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) |
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(rotary_emb): MistralRotaryEmbedding() |
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) |
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(mlp): MistralMLP( |
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(gate_proj): lora.Linear( |
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(base_layer): Linear(in_features=4096, out_features=14336, bias=False) |
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(lora_dropout): ModuleDict( |
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(default): Dropout(p=0.05, inplace=False) |
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) |
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(lora_A): ModuleDict( |
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(default): Linear(in_features=4096, out_features=64, bias=False) |
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) |
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(lora_B): ModuleDict( |
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(default): Linear(in_features=64, out_features=14336, bias=False) |
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) |
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(lora_embedding_A): ParameterDict() |
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(lora_embedding_B): ParameterDict() |
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) |
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(up_proj): lora.Linear( |
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(base_layer): Linear(in_features=4096, out_features=14336, bias=False) |
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(lora_dropout): ModuleDict( |
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(default): Dropout(p=0.05, inplace=False) |
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) |
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(lora_A): ModuleDict( |
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(default): Linear(in_features=4096, out_features=64, bias=False) |
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) |
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(lora_B): ModuleDict( |
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(default): Linear(in_features=64, out_features=14336, bias=False) |
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) |
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(lora_embedding_A): ParameterDict() |
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(lora_embedding_B): ParameterDict() |
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) |
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(down_proj): lora.Linear( |
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(base_layer): Linear(in_features=14336, out_features=4096, bias=False) |
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(lora_dropout): ModuleDict( |
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(default): Dropout(p=0.05, inplace=False) |
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) |
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(lora_A): ModuleDict( |
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(default): Linear(in_features=14336, out_features=64, bias=False) |
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) |
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(lora_B): ModuleDict( |
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(default): Linear(in_features=64, out_features=4096, bias=False) |
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) |
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(lora_embedding_A): ParameterDict() |
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(lora_embedding_B): ParameterDict() |
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) |
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(act_fn): SiLU() |
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) |
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(input_layernorm): MistralRMSNorm() |
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(post_attention_layernorm): MistralRMSNorm() |
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) |
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) |
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(norm): MistralRMSNorm() |
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(vision_clip_lmm_projector): Sequential( |
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(0): Linear(in_features=1024, out_features=4096, bias=True) |
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(1): GELU(approximate='none') |
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(2): Linear(in_features=4096, out_features=4096, bias=True) |
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) |
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) |
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(lm_head): Linear(in_features=4096, out_features=32000, bias=False) |
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) |
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) |
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) |
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``` |
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### Framework versions |
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- PEFT 0.10.0 |
