Error when attempting to specify vocabulary size in fastai text_classifier_learner with AWD_LTSM

gistfile1.txt

def train(arch, train_df=train_df, accum=1, epochs=12):
    dls = TextDataLoaders.from_df(train_df,text_col='desc',label_col='label',valid_pct=0.2,bs=64//accum)
    cbs = GradientAccumulation(64) if accum else []
    # learn = text_classifier_learner(dls, arch=AWD_LSTM, drop_mult=0.5, metrics=[accuracy], cbs=cbs).to_fp16()    
    learn = text_classifier_learner(dls, arch=AWD_LSTM(vocab_sz=200, emb_sz=20, n_hid=10, n_layers=2, pad_token=1, 
                                                       hidden_p=0.2, embed_p=0.02, input_p=0.1, weight_p=0.2), 
                                    drop_mult=0.5, metrics=[accuracy], cbs=cbs).to_fp16()    
    learn.fine_tune(epochs, 0.01)
    return learn

l = train(arch=AWD_LSTM, accum=2, epochs=4)

KeyError                                  Traceback (most recent call last)
/tmp/ipykernel_1867/573006035.py in <module>
     10     return learn
     11 
---> 12 l = train(arch=AWD_LSTM, accum=2, epochs=4)

/tmp/ipykernel_1867/573006035.py in train(arch, train_df, accum, epochs)
      5     learn = text_classifier_learner(dls, arch=AWD_LSTM(vocab_sz=200, emb_sz=20, n_hid=10, n_layers=2, pad_token=1, 
      6                                                        hidden_p=0.2, embed_p=0.02, input_p=0.1, weight_p=0.2), 
----> 7                                     drop_mult=0.5, metrics=[accuracy], cbs=cbs).to_fp16()    
      8     # learn = text_classifier_learner(dls, arch=LMModel6, drop_mult=0.5, metrics=[accuracy], cbs=cbs).to_fp16()
      9     learn.fine_tune(epochs, 0.01)

~/.local/lib/python3.7/site-packages/fastai/text/learner.py in text_classifier_learner(dls, arch, seq_len, config, backwards, pretrained, drop_mult, n_out, lin_ftrs, ps, max_len, y_range, **kwargs)
    260     assert n_out, "`n_out` is not defined, and could not be inferred from data, set `dls.c` or pass `n_out`"
    261     model = get_text_classifier(arch, len(vocab), n_out, seq_len=seq_len, config=config, y_range=y_range,
--> 262                                 drop_mult=drop_mult, lin_ftrs=lin_ftrs, ps=ps, max_len=max_len)
    263     meta = _model_meta[arch]
    264     learn = TextLearner(dls, model, splitter=meta['split_clas'], **kwargs)

~/.local/lib/python3.7/site-packages/fastai/text/models/core.py in get_text_classifier(arch, vocab_sz, n_class, seq_len, config, drop_mult, lin_ftrs, ps, pad_idx, max_len, y_range)
    159 ):
    160     "Create a text classifier from `arch` and its `config`, maybe `pretrained`"
--> 161     meta = _model_meta[arch]
    162     config = ifnone(config, meta['config_clas']).copy()
    163     for k in config.keys():

KeyError: AWD_LSTM(
  (encoder): Embedding(200, 20, padding_idx=1)
  (encoder_dp): EmbeddingDropout(
    (emb): Embedding(200, 20, padding_idx=1)
  )
  (rnns): ModuleList(
    (0): WeightDropout(
      (module): LSTM(20, 10, batch_first=True)
    )
    (1): WeightDropout(
      (module): LSTM(10, 20, batch_first=True)
    )
  )
  (input_dp): RNNDropout()
  (hidden_dps): ModuleList(
    (0): RNNDropout()
    (1): RNNDropout()
  )
)