Update requirements.txt

requirements.txt

@@ -1,37 +1,10 @@
-# Core ML/LLM Libraries
-# Note: torch should ideally be installed separately following PyTorch official instructions
-#       based on your CUDA version (if using GPU) for optimal performance.
-#       See: https://pytorch.org/get-started/locally/
 torch
-
-# Hugging Face libraries
-transformers>=4.38.0 # Gemma requires a recent version
-accelerate>=0.25.0 # Required by transformers and unsloth for optimized loading
-datasets # Often useful, though not strictly required by the script itself
-
-# Quantization library (needed for load_in_4bit=True)
-bitsandbytes>=0.41.3 # Check Unsloth docs for compatible versions if issues arise
-
-# Interface library
-gradio>=4.0.0 # Using a recent version
-
-# --- IMPORTANT ---
-# Unsloth needs to be installed separately following their specific instructions,
-# as it often involves non-standard pip commands (e.g., installing from GitHub)
-# or conda commands depending on your setup (CPU, CUDA version, ROCm).
-#
-# Example (check Unsloth's GitHub for the correct command for *your* system):
-# pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
-#
-# Or via Conda (check Unsloth docs):
-# conda install "unsloth::unsloth[conda-new]" # Example
-#
-# Because Unsloth is not listed here, you MUST install it manually *before*
-# trying to use this requirements.txt file or running the script.
-
-# Other common dependencies that might be implicitly needed
+transformers
+accelerate
+datasets
+bitsandbytes
+gradio
 Jinja2
 packaging
-# sentencepiece # Often used by tokenizers, good to include
-# protobuf # Sometimes needed by specific models/tokenizers
-unsloth
+unsloth
+gtts