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Makes Llama checkpoint convertion compatible with fused up/gate projection #26
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This was referenced Apr 17, 2024
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Thanks @evellasques for the PR. Going over it! |
HolySahar
reviewed
Apr 22, 2024
| "self_attention.core_attention.rotary_emb.inv_freq": (0, "self_attn.rotary_emb.inv_freq", None, 0), | ||
| "mlp.dense_h_to_4h.weight": (1, "mlp.gate_proj.weight", 0, 0), | ||
| "mlp.dense_h_to_4h_2.weight": (1, "mlp.up_proj.weight", 0, 0), | ||
| "mlp.dense_h_to_4h.weight": (1, "mlp.gate_proj_up_proj.weight", 0, 0), |
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why considering "gate" and "up" proj to be fused for HF checkpoint? Shouldn't you split them from nemo checkpoint instead and then save as separate "gate" and "up" params for HF?
| hf_model[hf_key_q], hf_model[hf_key_k], hf_model[hf_key_v] = torch.split(hf_model[hf_key], size_per_seg, dim=0) | ||
| hf_model.pop(hf_key) | ||
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| if "dense_h_to_4h" in k: |
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I think this is not accurate. "gate" and "proj" fusion is per tp rank in the nemo checkpoint. So, you can't first concatenate all tps and then split to "gate" and "proj". Instead you should split them for each tp rank.
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Issue #, 24
Description of changes:
Recent merging of up/down projection in Llama requires the equivalent merging in the HF to NeMo conversion scripts (and subsequent splitting in the NeMo to HF script).
This change fixes that for the following converters:
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