KeyError: <class 'transformers.models.falcon.configuration_falcon.FalconConfig'>`
Author: ishaansharma
Pull request: no

### System Info

- `transformers` version: 4.34.0.dev0
- Platform: Linux-6.2.0-31-generic-x86_64-with-glibc2.17
- Python version: 3.8.16
- Huggingface_hub version: 0.17.1
- Safetensors version: 0.3.3
- Accelerate version: 0.22.0
- Accelerate config: 	- compute_environment: LOCAL_MACHINE
	- distributed_type: NO
	- mixed_precision: fp16
	- use_cpu: False
	- debug: False
	- num_processes: 1
	- machine_rank: 0
	- num_machines: 1
	- gpu_ids: all
	- rdzv_backend: static
	- same_network: True
	- main_training_function: main
	- downcast_bf16: no
	- tpu_use_cluster: False
	- tpu_use_sudo: False
	- tpu_env: []
- PyTorch version (GPU?): 2.0.1+cu117 (True)
- Tensorflow version (GPU?): 2.10.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>

### Who can help?

@Narsil, @younesbelkada, @ArthurZucker

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

[Code from this post used for inference ](https://huggingface.co/blog/falcon#inference)

The when loading the tokenizer from_pretrained function using AutoTokenizer  class, I am getting an error that is restricting me to run the following code . 

```
from transformers import AutoTokenizer
import transformers
import torch

model = "my_finetuned_classification_model_folder_path"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-classification",
    model=model,
    tokenizer=tokenizer,
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
    device_map="auto",
)
```

The config file of the finetuned model is :
```
{
  "_name_or_path": "../model/hf_pretrain_tiny-random-falcon-7b_G5CST_15T_v1",
  "alibi": false,
  "apply_residual_connection_post_layernorm": false,
  "architectures": [
    "FalconForSequenceClassification"
  ],
  "attention_dropout": 0.0,
  "bias": false,
  "bos_token_id": 11,
  "eos_token_id": 11,
  "gradient_checkpointing": true,
  "hidden_dropout": 0.0,
  "hidden_size": 1136,
  "id2label": {
    "0": "LABEL_0",
    "1": "LABEL_1",
    "2": "LABEL_2",
    "3": "LABEL_3",
    "4": "LABEL_4",
    "5": "LABEL_5",
    "6": "LABEL_6",
    "7": "LABEL_7",
    "8": "LABEL_8",
    "9": "LABEL_9",
    "10": "LABEL_10",
    "11": "LABEL_11",
    "12": "LABEL_12",
    "13": "LABEL_13",
    "14": "LABEL_14"
  },
  "initializer_range": 0.02,
  "label2id": {
    "LABEL_0": 0,
    "LABEL_1": 1,
    "LABEL_10": 10,
    "LABEL_11": 11,
    "LABEL_12": 12,
    "LABEL_13": 13,
    "LABEL_14": 14,
    "LABEL_2": 2,
    "LABEL_3": 3,
    "LABEL_4": 4,
    "LABEL_5": 5,
    "LABEL_6": 6,
    "LABEL_7": 7,
    "LABEL_8": 8,
    "LABEL_9": 9
  },
  "layer_norm_epsilon": 1e-05,
  "max_position_embeddings": 2048,
  "model_type": "falcon",
  "multi_query": true,
  "new_decoder_architecture": false,
  "num_attention_heads": 71,
  "num_hidden_layers": 2,
  "num_kv_heads": 71,
  "pad_token_id": 11,
  "parallel_attn": true,
  "problem_type": "single_label_classification",
  "rope_scaling": null,
  "rope_theta": 10000.0,
  "torch_dtype": "float32",
  "transformers_version": "4.34.0.dev0",
  "use_cache": false,
  "vocab_size": 65024
}
```

### Expected behavior


The error that i got after running the code is as follows: 
````
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Input In [6], in <cell line: 1>()
----> 1 tokenizer = AutoTokenizer.from_pretrained(model_path)
3 pipeline = transformers.pipeline(
4 "text-classification",
5 model=model,
(...)
9 device_map="auto",
10 )

File ~/miniconda3/envs/ailab/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py:759, in AutoTokenizer.from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs)
757 model_type = config_class_to_model_type(type(config).name)
758 if model_type is not None:
--> 759 tokenizer_class_py, tokenizer_class_fast = TOKENIZER_MAPPING[type(config)]
760 if tokenizer_class_fast and (use_fast or tokenizer_class_py is None):
761 return tokenizer_class_fast.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)

File ~/miniconda3/envs/ailab/lib/python3.8/site-packages/transformers/models/auto/auto_factory.py:745, in _LazyAutoMapping.getitem(self, key)
743 model_name = self._model_mapping[mtype]
744 return self._load_attr_from_module(mtype, model_name)
--> 745 raise KeyError(key)

KeyError: <class 'transformers.models.falcon.configuration_falcon.FalconConfig'>
````


Comments:
Hey! Could you share the ` tokenizer_config.json`  or ` tokenizer.json`  files? 

This is the tokenizer_config.json content : 

```
{
  "add_prefix_space": false,
  "additional_special_tokens": [
    ">>TITLE<<",
    ">>ABSTRACT<<",
    ">>INTRODUCTION<<",
    ">>SUMMARY<<",
    ">>COMMENT<<",
    ">>ANSWER<<",
    ">>QUESTION<<",
    ">>DOMAIN<<",
    ">>PREFIX<<",
    ">>SUFFIX<<",
    ">>MIDDLE<<"
  ],
  "clean_up_tokenization_spaces": true,
  "eos_token": "
",
  "model_input_names": [
    "input_ids",
    "attention_mask"
  ],
  "model_max_length": 2048,
  "tokenizer_class": "PreTrainedTokenizerFast"
}
```

You are trying to use the `PreTrainedTokenizerFast` without any `tokenizer.json` file. Since there is no mapping for falcon, it's gonna be a bit hard.  Need to have a `tokenizer.json` file. Otherwise it should try to initialised  a slow tokenizer and then convert it, which should work even if there is no mapping. 

KeyError: <class 'transformers.models.table_transformer.configuration_table_transformer.TableTransformerConfig'>