diff --git a/whisper/transcribe.py b/whisper/transcribe.py
index 3c510e7..f25dd35 100644
--- a/whisper/transcribe.py
+++ b/whisper/transcribe.py
@@ -42,7 +42,7 @@ def transcribe(
     verbose: Optional[bool] = None,
     temperature: Union[float, Tuple[float, ...]] = (0.0, 0.2, 0.4, 0.6, 0.8, 1.0),
     compression_ratio_threshold: Optional[float] = 2.4,
-    compression_ratio_halucination_threshold: Optional[float] = 3,
+    compression_ratio_hallucination_threshold: Optional[float] = 3,
     logprob_threshold: Optional[float] = -1.0,
     no_speech_threshold: Optional[float] = 0.6,
     condition_on_previous_text: bool = True,
@@ -76,7 +76,7 @@ def transcribe(
     compression_ratio_threshold: float
         If the gzip compression ratio is above this value, treat as failed
 
-    compression_ratio_halcination_threshold: float
+    compression_ratio_hallucination_threshold: float
         If the gzip compression ratio is above this value after all attempts to decode, treat as a halucination and skip
 
     logprob_threshold: float
@@ -106,11 +106,6 @@ def transcribe(
         "prompt-engineer" a context for transcription, e.g. custom vocabularies or proper nouns
         to make it more likely to predict those word correctly.
 
-    carry_initial_prompt: bool
-        If carry_initial_prompt is True, `initial_prompt` is prepended to the prompt of each internal
-        `decode()` call. If there is not enough context space at the start of the prompt, it is
-        left-sliced to make space.
-
     decode_options: dict
         Keyword arguments to construct `DecodingOptions` instances
 
@@ -220,12 +215,14 @@ def transcribe(
             ):
                 needs_fallback = False  # silence
             if (
-            compression_ratio_halucination_threshold is not None
-            and decode_result.compression_ratio > compression_ratio_halucination_threshold
+            compression_ratio_hallucination_threshold is not None
+            and decode_result.compression_ratio > compression_ratio_hallucination_threshold
             and t == temperatures[-1]
             ):
             # Discard the segment
                 continue  # Skip to the next segment
+
+
             if not needs_fallback:
                 break
 
@@ -243,11 +240,9 @@ def transcribe(
     all_segments = []
     prompt_reset_since = 0
 
-    remaining_prompt_length = model.dims.n_text_ctx // 2 - 1
     if initial_prompt is not None:
         initial_prompt_tokens = tokenizer.encode(" " + initial_prompt.strip())
         all_tokens.extend(initial_prompt_tokens)
-        remaining_prompt_length -= len(initial_prompt_tokens)
     else:
         initial_prompt_tokens = []
 
@@ -293,13 +288,7 @@ def transcribe(
             segment_duration = segment_size * HOP_LENGTH / SAMPLE_RATE
             mel_segment = pad_or_trim(mel_segment, N_FRAMES).to(model.device).to(dtype)
 
-            if carry_initial_prompt:
-                nignored = max(len(initial_prompt_tokens), prompt_reset_since)
-                remaining_prompt = all_tokens[nignored:][-remaining_prompt_length:]
-                decode_options["prompt"] = initial_prompt_tokens + remaining_prompt
-            else:
-                decode_options["prompt"] = all_tokens[prompt_reset_since:]
-
+            decode_options["prompt"] = all_tokens[prompt_reset_since:]
             result: DecodingResult = decode_with_fallback(mel_segment)
             tokens = torch.tensor(result.tokens)
 
@@ -553,8 +542,6 @@ def cli():
 
     parser.add_argument("--suppress_tokens", type=str, default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations")
     parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.")
-    parser.add_argument("--carry_initial_prompt", type=str2bool, default=False, help="if True, prepend initial_prompt to every internal decode() call. May reduce the effectiveness of condition_on_previous_text")
-
     parser.add_argument("--condition_on_previous_text", type=str2bool, default=True, help="if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop")
     parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default")