36 lines
1.2 KiB
Markdown
36 lines
1.2 KiB
Markdown
---
|
|
library_name: transformers
|
|
tags:
|
|
- custom_generate
|
|
---
|
|
|
|
## Description
|
|
Example repository used to document `generate` from the hub. It is a simplified implementation of greedy decoding.
|
|
|
|
## Base model:
|
|
`Qwen/Qwen2.5-0.5B-Instruct`
|
|
|
|
## Model compatibility
|
|
Most models. More specifically, any `transformer` LLM/VLM trained for causal language modeling.
|
|
|
|
## Additional Arguments
|
|
`left_padding` (`int`, *optional*): number of padding tokens to add before the provided input
|
|
|
|
## Output Type changes
|
|
(none)
|
|
|
|
## Example usage
|
|
|
|
```py
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
|
|
|
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct")
|
|
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct", device_map="auto")
|
|
|
|
inputs = tokenizer(["The quick brown"], return_tensors="pt").to(model.device)
|
|
# There is a print message hardcoded in the custom generation method
|
|
gen_out = model.generate(**inputs, left_padding=5, custom_generate="transformers-community/custom_generate_example", trust_remote_code=True)
|
|
print(tokenizer.batch_decode(gen_out)) # don't skip special tokens
|
|
#['<|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|>The quick brown fox jumps over the lazy dog.\n\nThe sentence "The quick']
|
|
```
|