HuggingFacePipeline is not loaded correctly

### System Info

langchain==0.0.186

### Who can help?

@hwchase17

### Information

- [X] The official example notebooks/scripts
- [ ] My own modified scripts

### Related Components

- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [X] Chains
- [ ] Callbacks/Tracing
- [ ] Async

### Reproduction

Running the following code snippet:
```python
from langchain import HuggingFacePipeline

llm = HuggingFacePipeline.from_model_id(model_id="bigscience/bloom-1b7", task="text-generation", model_kwargs={"temperature":0, "max_length":64})

from langchain import PromptTemplate,  LLMChain

template = """Question: {question}

Answer: Let's think step by step."""
prompt = PromptTemplate(template=template, input_variables=["question"])

llm_chain = LLMChain(prompt=prompt, llm=llm)
llm_chain.save("/tmp/hfp/model.yaml")
from langchain.chains.loading import load_chain
local_loaded_model = load_chain("/tmp/hfp/model.yaml")
question = "What is electroencephalography?"
local_loaded_model.run(question)
```
Gives the following error:
```
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
File <command-826248432925795>:1
----> 1 local_loaded_model.run(question)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/chains/base.py:236, in Chain.run(self, callbacks, *args, **kwargs)
    234     if len(args) != 1:
    235         raise ValueError("`run` supports only one positional argument.")
--> 236     return self(args[0], callbacks=callbacks)[self.output_keys[0]]
    238 if kwargs and not args:
    239     return self(kwargs, callbacks=callbacks)[self.output_keys[0]]

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/chains/base.py:140, in Chain.__call__(self, inputs, return_only_outputs, callbacks)
    138 except (KeyboardInterrupt, Exception) as e:
    139     run_manager.on_chain_error(e)
--> 140     raise e
    141 run_manager.on_chain_end(outputs)
    142 return self.prep_outputs(inputs, outputs, return_only_outputs)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/chains/base.py:134, in Chain.__call__(self, inputs, return_only_outputs, callbacks)
    128 run_manager = callback_manager.on_chain_start(
    129     {"name": self.__class__.__name__},
    130     inputs,
    131 )
    132 try:
    133     outputs = (
--> 134         self._call(inputs, run_manager=run_manager)
    135         if new_arg_supported
    136         else self._call(inputs)
    137     )
    138 except (KeyboardInterrupt, Exception) as e:
    139     run_manager.on_chain_error(e)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/chains/llm.py:69, in LLMChain._call(self, inputs, run_manager)
     64 def _call(
     65     self,
     66     inputs: Dict[str, Any],
     67     run_manager: Optional[CallbackManagerForChainRun] = None,
     68 ) -> Dict[str, str]:
---> 69     response = self.generate([inputs], run_manager=run_manager)
     70     return self.create_outputs(response)[0]

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/chains/llm.py:79, in LLMChain.generate(self, input_list, run_manager)
     77 """Generate LLM result from inputs."""
     78 prompts, stop = self.prep_prompts(input_list, run_manager=run_manager)
---> 79 return self.llm.generate_prompt(
     80     prompts, stop, callbacks=run_manager.get_child() if run_manager else None
     81 )

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/llms/base.py:134, in BaseLLM.generate_prompt(self, prompts, stop, callbacks)
    127 def generate_prompt(
    128     self,
    129     prompts: List[PromptValue],
    130     stop: Optional[List[str]] = None,
    131     callbacks: Callbacks = None,
    132 ) -> LLMResult:
    133     prompt_strings = [p.to_string() for p in prompts]
--> 134     return self.generate(prompt_strings, stop=stop, callbacks=callbacks)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/llms/base.py:191, in BaseLLM.generate(self, prompts, stop, callbacks)
    189 except (KeyboardInterrupt, Exception) as e:
    190     run_manager.on_llm_error(e)
--> 191     raise e
    192 run_manager.on_llm_end(output)
    193 return output

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/llms/base.py:185, in BaseLLM.generate(self, prompts, stop, callbacks)
    180 run_manager = callback_manager.on_llm_start(
    181     {"name": self.__class__.__name__}, prompts, invocation_params=params
    182 )
    183 try:
    184     output = (
--> 185         self._generate(prompts, stop=stop, run_manager=run_manager)
    186         if new_arg_supported
    187         else self._generate(prompts, stop=stop)
    188     )
    189 except (KeyboardInterrupt, Exception) as e:
    190     run_manager.on_llm_error(e)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/llms/base.py:436, in LLM._generate(self, prompts, stop, run_manager)
    433 new_arg_supported = inspect.signature(self._call).parameters.get("run_manager")
    434 for prompt in prompts:
    435     text = (
--> 436         self._call(prompt, stop=stop, run_manager=run_manager)
    437         if new_arg_supported
    438         else self._call(prompt, stop=stop)
    439     )
    440     generations.append([Generation(text=text)])
    441 return LLMResult(generations=generations)

File /local_disk0/.ephemeral_nfs/envs/pythonEnv-51383c0b-9b1f-48ec-a6a9-ac979dcdc755/lib/python3.10/site-packages/langchain/llms/huggingface_pipeline.py:168, in HuggingFacePipeline._call(self, prompt, stop, run_manager)
    162 def _call(
    163     self,
    164     prompt: str,
    165     stop: Optional[List[str]] = None,
    166     run_manager: Optional[CallbackManagerForLLMRun] = None,
    167 ) -> str:
--> 168     response = self.pipeline(prompt)
    169     if self.pipeline.task == "text-generation":
    170         # Text generation return includes the starter text.
    171         text = response[0]["generated_text"][len(prompt) :]

TypeError: 'NoneType' object is not callable
```

### Expected behavior

`local_loaded_model.run(question)` should behave the same way as:
```python
llm_chain.run(question)
```