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---
library_name: transformers
license: apache-2.0
---
# WestLake-7B-v2-laser-truthy-dpo
## Process
+ Trained [cognitivecomputations/WestLake-7B-v2-laser](https://huggingface.co/cognitivecomputations/WestLake-7B-v2-laser) on jondurbin/truthy-dpo-v0.1
+ Completed 2 epochs
+ 2e-5 learning rate
## Code Example
```python
from transformers import AutoTokenizer
import transformers
import torch
model = "macadeliccc/WestLake-7B-v2-laser-truthy-dpo"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
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"])
```
## Evaluations
Evaluated the GGUF for usability reasons. EQ-Bench uses Ooba for inference.
<pre>----Benchmark Complete----
2024-01-31 14:38:14
Time taken: 18.9 mins
Prompt Format: ChatML
Model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo-GGUF
Score (v2): 75.15
Parseable: 171.0
---------------
Batch completed
Time taken: 19.0 mins
---------------
</pre>
## GGUF
GGUF versions are available [here](https://huggingface.co/macadeliccc/WestLake-7B-v2-laser-truthy-dpo-GGUF) |