| | --- |
| | tags: |
| | - autotrain |
| | - text-generation-inference |
| | - text-generation |
| | - peft |
| | library_name: transformers |
| | 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) |
| | ``` |