--- library_name: peft widget: - text: >- Claire makes a 3 egg omelet every morning for breakfast. How many dozens of eggs will she eat in 4 weeks? example_title: Solve math pipeline_tag: text-generation license: apache-2.0 datasets: - gsm8k language: - en --- ## Usage ```python from peft import PeftModel, PeftConfig from transformers import AutoModelForCausalLM config = PeftConfig.from_pretrained("mwitiderrick/zephyr-7b-beta-gsm8k") model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(model, "mwitiderrick/zephyr-7b-beta-gsm8k") prompt = "James decides to run 3 sprints 3 times a week. He runs 60 meters each sprint. How many total meters does he run a week?" pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200) result = pipe(f"[INST] {prompt} [/INST]") print(result[0]['generated_text']) """ [INST] Claire makes a 3 egg omelet every morning for breakfast. How many dozens of eggs will she eat in 4 weeks? [/INST] She eats 3*7=<<3*7=21>>21 eggs a week So she eats 21*4=<<21*4=84>>84 eggs in 4 weeks That means she eats 84/12=<<84/12=7>>7 dozen eggs """ ``` ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: bfloat16 The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.5.0 - PEFT 0.5.0