---
library_name: transformers
tags:
- unsloth
datasets:
- AIForge/OpenHermes-vi-filtered
language:
- vi
---

# 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.

- **Developed by:** thangvip
- **Language(s) (NLP):** Vietnamese
- **Finetuned from model:** vietgpt/Sailor-1.8B

### Model Sources [optional]

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## Uses

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

model = AutoModelForCausalLM.from_pretrained("thangvip/vilord-1.8B-instruct", device_map="auto", cache_dir="./cache").eval()

tokenizer = AutoTokenizer.from_pretrained("thangvip/vilord-1.8B-instruct", cache_dir="./cache")


messages = [
  {'role': 'system', 'content': "bạn là trợ lý AI hữu ích"},
  {"role": "user", "content": "Nước nào có diện tích lớn nhất?"},
]
text = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
print(text)
inputs = tokenizer(text, return_tensors="pt")
inputs = {k: v.to("cuda") for k, v in inputs.items()}

outputs = model.generate(**inputs, tokenizer=tokenizer, max_new_tokens=256, do_sample=True, top_p=0.95, temperature=0.1, repetition_penalty=1.2, eos_token_id=tokenizer.eos_token_id, stop_strings=['<|im_end|>'])
print(tokenizer.decode(outputs[0]))
```

### 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

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## Training Details

### Training Data

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### Training Procedure

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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

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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).

- **Hardware Type:** [More Information Needed]
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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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## Model Card Authors [optional]

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