tags: | |
- autotrain | |
- text-generation-inference | |
- text-generation | |
- peft | |
library_name: transformers | |
base_model: meta-llama/Llama-2-7b-hf | |
widget: | |
- messages: | |
- role: user | |
content: What is your favorite condiment? | |
license: other | |
# Model Trained Using AutoTrain | |
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain). | |
# Usage | |
```python | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
model_path = "PATH_TO_THIS_REPO" | |
tokenizer = AutoTokenizer.from_pretrained(model_path) | |
model = AutoModelForCausalLM.from_pretrained( | |
model_path, | |
device_map="auto", | |
torch_dtype='auto' | |
).eval() | |
# Prompt content: "hi" | |
messages = [ | |
{"role": "user", "content": "hi"} | |
] | |
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt') | |
output_ids = model.generate(input_ids.to('cuda')) | |
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True) | |
# Model response: "Hello! How can I assist you today?" | |
print(response) | |
``` |