Quantized checkpoint support in export and deploy modules
jenkins
# What does this PR do ?

Add support for testing, deploying and running quantized "qnemo" checkpoints in `nemo.deploy` and `nemo.export` modules.

**Collection**: NLP

# Changelog 
- qnemo support
- bump ammo version to 0.9.4
- update code for trt-llm 0.9.0
- Lambada evaluation setup
- timing of evaluation (with minor improvements)
- documentation

# Usage

Building TensorRT-LLM engine and running a basic prompt:
```python
from nemo.export import TensorRTLLM


trt_llm_exporter = TensorRTLLM(model_dir="/path/to/trt_llm_engine_folder")
trt_llm_exporter.export(
    nemo_checkpoint_path="/path/to/qnemo/ckpt.qnemo",
    model_type="llama",
    n_gpus=1,
)
output = trt_llm_exporter.forward(["Hi, how are you?", "I am good, thanks, how about you?"])
```

Running Lambada test locally:
```python
python tests/export/test_nemo_export.py \
  --model_name local \
  --model_type llama \
  --checkpoint_dir /path/to/qnemo/ckpt.qnemo \
  --trt_llm_model_dir /path/to/trt_llm_engine_folder \
  --min_gpus 1 \
  --run_accuracy \
  --test_deployment True \
  --test_data_path lambada.json
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

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- [x] Did you add or update any necessary documentation?
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  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [x] Documentation

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# Additional Information
* Related to https://github.com/NVIDIA/NeMo/pull/8743
