[`RWKV`] Fix RWKV 4bit
# What does this PR do?

Fixes RWKV 4bit inference. 
Fixes https://github.com/huggingface/transformers/issues/23848

```python
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_id = "RWKV/rwkv-4-1b5-pile"

model = AutoModelForCausalLM.from_pretrained(model_id, load_in_4bit=True, device_map={"":0})
tokenizer = AutoTokenizer.from_pretrained(model_id)

generation_config = GenerationConfig(max_new_tokens=20, pad_token_id=tokenizer.eos_token_id)
question = "Hello my name is Younes"
inputs = tokenizer(question, return_tensors="pt").to(0)
output_int8 = model.generate((inputs["input_ids"]), generation_config=generation_config)
print(tokenizer.decode(output_int8[0], skip_special_tokens=True))
>>> Hello my name is Younes and I am from the United States. I am in the process of applying to the University of California,
```

The fix is similar to 8bit linear layers, one needs to rescale the quantization statistics of the fp4 linear layers

cc @sgugger 
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