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Fixed Sequence Classification errors, loaded model weirdly (#2793)

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pluesclues 2025-06-23 21:56:56 -04:00 • committed by GitHub
commit 1fc64a0a1b
1 changed files with 8 additions and 9 deletions
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17
unsloth/models/llama.py
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@ -69,7 +69,7 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, AutoModelForSequen
from transformers.models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING
from transformers import set_seed as transformers_set_seed
from peft import LoraConfig, TaskType, get_peft_model as _get_peft_model
from peft import PeftModelForCausalLM
from peft import PeftModelForCausalLM, PeftModelForSequenceClassification
from ..save import patch_saving_functions
import re, os, inspect, math, sys
import types
@ -762,8 +762,7 @@ def LlamaModel_fast_forward(
# Ignore attention_mask
if attention_mask is None:
padding_mask = None
elif self.training:
# elif attention_mask is None:
elif self.training and os.environ.get("UNSLOTH_KEEP_PADDING", "0") != '1':
attention_mask = None
padding_mask = None
else:
@ -2079,7 +2078,8 @@ class FastLlamaModel:
model.for_inference = functools.partial(FastLlamaModel.for_inference, model)
# Patch generate
if model.generate.__name__ != "unsloth_fast_generate":
is_classification = "Classification" in str(type(model))
if not is_classification and model.generate.__name__ != "unsloth_fast_generate":
model._old_generate = model.generate
unsloth_fast_generate.__doc__ = model._old_generate.__doc__
model.generate = types.MethodType(unsloth_fast_generate, model)
@ -2159,7 +2159,7 @@ class FastLlamaModel:
if r <= 0:
raise TypeError(f"Unsloth: Rank of {str(r)} must be larger than 0.")
if isinstance(model, PeftModelForCausalLM):
if isinstance(model, PeftModelForCausalLM) or isinstance(model, PeftModelForSequenceClassification):
# Check if exactly the same and then pass through!
assert(hasattr(model, "peft_config"))
@ -2428,7 +2428,7 @@ class FastLlamaModel:
is_classification = "Classification" in str(type(model))
# Get LoRA
# if not is_classification else TaskType.SEQ_CLS
#
arguments = dict(
r = r,
@ -2436,7 +2436,7 @@ class FastLlamaModel:
target_modules = final_modules,
lora_dropout = lora_dropout,
bias = bias,
task_type = TaskType.CAUSAL_LM,
task_type = TaskType.CAUSAL_LM if not is_classification else TaskType.SEQ_CLS,
layers_to_transform = layers_to_transform,
init_lora_weights = init_lora_weights,
loftq_config = loftq_config,
@ -2450,7 +2450,6 @@ class FastLlamaModel:
_saved_temp_tokenizer = model._saved_temp_tokenizer
lora_config = LoraConfig(**arguments)
# First offload lm_head and embed_tokens to disk
input_embeddings_device = model.get_input_embeddings().weight.device
if is_classification:
@ -2572,7 +2571,7 @@ class FastLlamaModel:
use_gradient_checkpointing = use_gradient_checkpointing,
)
pass
if not isinstance(model, PeftModelForCausalLM):
if not isinstance(model, PeftModelForCausalLM) and not isinstance(model, PeftModelForSequenceClassification):
raise TypeError(
"Unsloth: Your model needs to call `.get_peft_model` first!"
)