metadata

library_name: transformers
license: apache-2.0

WestLake-7B-v2-laser-truthy-dpo

Process

Trained cognitivecomputations/WestLake-7B-v2-laser on jondurbin/truthy-dpo-v0.1
Completed 2 epochs
2e-5 learning rate

Code Example

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "macadeliccc/WestLake-7B-v2-laser-truthy-dpo"
tokenizer = AutoTokenizer.from_pretrained(model_id)

model = AutoModelForCausalLM.from_pretrained(model_id)

text = "Create an idea for a TV show and write a short pilot script"
inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs, max_new_tokens=4096)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Evaluations

Evaluated the GGUF for usability reasons. EQ-Bench uses Ooba for inference.

----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
---------------

GGUF

GGUF versions are available here