|
--- |
|
tags: |
|
- autotrain |
|
- text-generation |
|
widget: |
|
- text: "I love AutoTrain because " |
|
license: other |
|
base_model: mistralai/Mistral-7B-Instruct-v0.2 |
|
--- |
|
|
|
# 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) |
|
``` |
