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--- |
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license: apache-2.0 |
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dataset: yield |
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tags: |
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- finetuned |
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- multimodal |
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inference: false |
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--- |
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These are weights for a version of `checkpoints/stage2/llava-moleculestm-vicuna-7b-v1.5-pretrain_all` finetuned for multimodal applications. |
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### Modalities |
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* Molecule2DModality (use `<molecule_2d>` in text and provide `molecules` |
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### Usage |
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GitHub: https://github.com/IDEA-XL/PRESTO (includes training scripts and basic inference server) |
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### Dataset |
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yield (9515 examples) |
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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 RTX A6000, 00000000:01:00.0, 94.02.5C.00.02 |
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NVIDIA RTX A6000, 00000000:25:00.0, 94.02.5C.00.02 |
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NVIDIA RTX A6000, 00000000:41:00.0, 94.02.5C.00.02 |
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NVIDIA RTX A6000, 00000000:61:00.0, 94.02.5C.00.02 |
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NVIDIA RTX A6000, 00000000:81:00.0, 94.02.5C.00.02 |
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NVIDIA RTX A6000, 00000000:A1:00.0, 94.02.5C.00.02 |
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NVIDIA RTX A6000, 00000000:C1:00.0, 94.02.5C.00.02 |
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NVIDIA RTX A6000, 00000000:E1:00.0, 94.02.5C.00.02 |
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``` |
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### Model |
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``` |
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LlamaLMMForCausalLM.model = |
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LlamaLMMForCausalLM( |
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(model): LlamaLMMModel( |
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(embed_tokens): Embedding(32000, 4096, padding_idx=0) |
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(layers): ModuleList( |
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(0-31): 32 x LlamaDecoderLayer( |
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(self_attn): LlamaSdpaAttention( |
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(q_proj): Linear(in_features=4096, out_features=4096, bias=False) |
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(k_proj): Linear(in_features=4096, out_features=4096, bias=False) |
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(v_proj): Linear(in_features=4096, out_features=4096, bias=False) |
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(o_proj): Linear(in_features=4096, out_features=4096, bias=False) |
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(rotary_emb): LlamaRotaryEmbedding() |
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) |
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(mlp): LlamaMLP( |
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(gate_proj): Linear(in_features=4096, out_features=11008, bias=False) |
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(up_proj): Linear(in_features=4096, out_features=11008, bias=False) |
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(down_proj): Linear(in_features=11008, out_features=4096, bias=False) |
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(act_fn): SiLU() |
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) |
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(input_layernorm): LlamaRMSNorm() |
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(post_attention_layernorm): LlamaRMSNorm() |
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) |
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) |
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(norm): LlamaRMSNorm() |
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(molecule_2d_lmm_projector): _MLPVectorProjector( |
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(mlp): Sequential( |
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(0): Linear(in_features=300, 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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) |
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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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