---
library_name: transformers
tags: []
---

# Model Card for Model ID

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## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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## Uses

```python


%%time

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")

from peft import PeftModel
model_name='google/gemma-2b'
inference_model = AutoModelForCausalLM.from_pretrained(
    model_name,
    low_cpu_mem_usage=True,
    # use_flash_attention_2=True,
   
)
inference_model.resize_token_embeddings(len(tokenizer))

inference_model = PeftModel.from_pretrained(inference_model, "hemanthkandimalla/HemanthLLM_tiny1.1b")

inference_model.eval()
text="attacks names"
tokenizer_input=tokenizer(text=text, return_tensors="pt")
output_tokens = inference_model.generate(
    **tokenizer_input,
    max_new_tokens=256,
    do_sample=True,
    temperature=0.2,
    top_p=0.95,
    top_k=50,
    eos_token_id=tokenizer.eos_token_id,
    pad_token_id=tokenizer.pad_token_id,
)
text=tokenizer.decode(output_tokens[0], skip_special_tokens=False)

print(text)

```
### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure 

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

### Model Architecture and Objective

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#### Hardware

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## Citation [optional]

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## Glossary [optional]

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