TL;DR: `pip install torch` (or tensorflow/flax, pick your backend). transformers needs at least one deep learning backend at import time. The pip install of transformers alone does not pull in torch. If torch is installed, you have an environment mismatch, install it with the same python you run.

The error:
```text
ImportError: transformers requires the PyTorch library but it was not found in your environment. Please install torch or tensorflow or flax.
```

## Fix
1. Run `python -c "import torch"`
   Expected: ImportError confirms torch is missing from this interpreter
2. Install: `python -m pip install torch` (CPU) or the CUDA wheel from pytorch.org
   Expected: Successfully installed torch
3. Re-run your transformers import
   Expected: no ImportError, transformers loads

## When this applies
- the full error text about transformers requiring torch/tensorflow/flax
- you installed only `pip install transformers`

## When this does not apply
- No module named 'transformers' (install transformers itself)
- a specific name like AutoModel fails to import (different problem)

## Version compatibility
transformers 4.x with any backend. Error raised by transformers' dependency check in __init__.

## Why it happens
transformers lazily requires one of torch, tensorflow, or flax. The PyPI package declares them as optional extras, so a bare `pip install transformers` leaves you with none and the import guard fires.

## Edge cases
- `pip install transformers[torch]` pulls the backend in one step.
- If you only need tokenizers, that subpackage imports fine without a backend.
- Same guard exists for tensorflow and flax variants of the message.