| | --- |
| | license: cc-by-nc-4.0 |
| | tags: |
| | - moe |
| | - dpo |
| | --- |
| | |
| | # DPO of cloudyu/Mixtral_7Bx2_MoE |
| |
|
| | dataset : jondurbin/truthy-dpo-v0.1 |
| |
|
| | * metrics average 75.88 |
| | * TruthfulQA 81.5 SOTA (2024-01-17) |
| |
|
| | gpu code example |
| |
|
| | ``` |
| | import torch |
| | from transformers import AutoTokenizer, AutoModelForCausalLM |
| | import math |
| | |
| | ## v2 models |
| | model_path = "cloudyu/Mixtral_7Bx2_MoE_DPO" |
| | |
| | tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False) |
| | model = AutoModelForCausalLM.from_pretrained( |
| | model_path, torch_dtype=torch.bfloat16, device_map='auto',local_files_only=False, load_in_4bit=True |
| | ) |
| | print(model) |
| | prompt = input("please input prompt:") |
| | while len(prompt) > 0: |
| | input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cuda") |
| | |
| | generation_output = model.generate( |
| | input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2 |
| | ) |
| | print(tokenizer.decode(generation_output[0])) |
| | prompt = input("please input prompt:") |
| | ``` |
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