Introducing Yi-9B-Forest-DPO, a LLM fine-tuned with base model 01-ai/Yi-9B, using direct preference optimization.
This model showcases exceptional prowess across a spectrum of natural language processing (NLP) tasks.
A mixture of the following datasets was used for fine-tuning.
Intel/orca_dpo_pairs
nvidia/HelpSteer
jondurbin/truthy-dpo-v0.1
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "abhishekchohan/Yi-9B-Forest-DPO"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Runs of abhishekchohan Yi-9B-Forest-DPO on huggingface.co
75
Total runs
-2
24-hour runs
-2
3-day runs
-2
7-day runs
-9
30-day runs
More Information About Yi-9B-Forest-DPO huggingface.co Model
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Yi-9B-Forest-DPO is an open source model from GitHub that offers a free installation service, and any user can find Yi-9B-Forest-DPO on GitHub to install. At the same time, huggingface.co provides the effect of Yi-9B-Forest-DPO install, users can directly use Yi-9B-Forest-DPO installed effect in huggingface.co for debugging and trial. It also supports api for free installation.