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Update llama.py

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Daniel Han 2024-12-26 19:16:58 -08:00
commit 1f81f9f5ab
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unsloth/models/llama.py
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@ -1009,7 +1009,6 @@ def CausalLM_fast_forward(fast_forward_inference):
if not RETURN_LOGITS and HAS_CUT_CROSS_ENTROPY and labels is not None:
n_items = kwargs.get("num_items_in_batch", None) or kwargs.get("n_items", None)
print(0, n_items)
loss = fused_linear_cross_entropy(
hidden_states = hidden_states,
lm_weight = lm_head,
@ -1056,7 +1055,6 @@ def CausalLM_fast_forward(fast_forward_inference):
# Fixes https://github.com/unslothai/unsloth/issues/10
self.extra_ignored_labels = torch.full((self.max_seq_length, 1), -100, device = "cuda:0")
pass
print(1, kwargs.get("num_items_in_batch", None) or kwargs.get("n_items", None))
shift_labels = torch.hstack((labels[..., 1:], self.extra_ignored_labels[:labels.shape[0]]))
loss = fast_cross_entropy_loss(
logits = shift_logits,