|
--- |
|
license: mit |
|
language: |
|
- en |
|
base_model: |
|
- Qwen/Qwen2.5-32B-Instruct |
|
pipeline_tag: text-generation |
|
--- |
|
|
|
# Apollo Model |
|
|
|
This is an experimental hybrid reasoning model built on Qwen2.5-32B-Instruct |
|
|
|
# GGUF |
|
|
|
mradermacher/Apollo-v3-32B-GGUF |
|
|
|
thanks mradermacher for this gguf |
|
|
|
### Merge Method |
|
|
|
This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) as a base. |
|
|
|
|
|
### Enable reasoning |
|
|
|
prompt the LLM with think deeper and step by step |
|
|
|
### Example code |
|
|
|
``` |
|
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
|
model_name = "rootxhacker/Apollo-v3-32B" |
|
|
|
model = AutoModelForCausalLM.from_pretrained( |
|
model_name, |
|
torch_dtype="auto", |
|
device_map="auto" |
|
) |
|
tokenizer = AutoTokenizer.from_pretrained(model_name) |
|
|
|
prompt = "How many r's are in the word strawberry" |
|
messages = [ |
|
{"role": "user", "content": prompt} |
|
] |
|
text = tokenizer.apply_chat_template( |
|
messages, |
|
tokenize=False, |
|
add_generation_prompt=True |
|
) |
|
|
|
model_inputs = tokenizer([text], return_tensors="pt").to(model.device) |
|
|
|
generated_ids = model.generate( |
|
**model_inputs, |
|
max_new_tokens=32768 |
|
) |
|
generated_ids = [ |
|
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
|
] |
|
|
|
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
|
print(response) |
|
|
|
``` |
