RichardErkhov/crumb_-_apricot-wildflower-20-gguf

Quantization made by Richard Erkhov.

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apricot-wildflower-20 - GGUF

• —Model creator: https://huggingface.co/crumb/
• —Original model: https://huggingface.co/crumb/apricot-wildflower-20/

Original model description: --- license: apache-2.0 model-index:

• —name: apricot-wildflower-20 results:
• —task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2arc config: ARC-Challenge split: test args: numfew_shot: 25 metrics:
• —type: accnorm value: 59.64 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=crumb/apricot-wildflower-20 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: numfewshot: 10 metrics:
• —type: accnorm value: 81.76 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllm_leaderboard?query=crumb/apricot-wildflower-20 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: numfewshot: 5 metrics:
• —type: acc value: 63.38 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=crumb/apricot-wildflower-20 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthfulqa config: multiplechoice split: validation args: numfewshot: 0 metrics:
• —type: mc2 value: 41.76 source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=crumb/apricot-wildflower-20 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winograndexl split: validation args: numfew_shot: 5 metrics:
• —type: acc value: 77.9 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=crumb/apricot-wildflower-20 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: numfewshot: 5 metrics:
• —type: acc value: 33.97 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=crumb/apricot-wildflower-20 name: Open LLM Leaderboard ---

apricot-wildflower-20

This model is the Mistral-7b model finetuned for 1k steps with a combined lm loss and distillation loss on Openwebtext2 with a >=20 reddit score filter with training logits from Mixtral. I'm not going to pretend it was a big project I did it in a dream and woke up and replicated the code without any actual reason, idk how well it fares in benchmarks.

(update: not very good)

use

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "crumb/apricot-wildflower-20"
tokenizer = AutoTokenizer.from_pretrained(model_id)

model = AutoModelForCausalLM.from_pretrained(model_id, low_cpu_mem_usage=True, device_map="auto", load_in_8bit=True)

text = "Hello my name is"
inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
# Hello my name is Katie and I am a 20 year old student from the UK. I am currently studying for a degree in English Literature and Creative Writing at the University of Leeds. I am a huge fan of the Harry Potter series and have been since I was 10 years old. I have read the books countless times and have seen the films many times too. I am a huge fan of the Harry Potter fandom and have been a member of the Harry Potter forums for a few years now. I am also a member of the Harry Potter fan club and have been for a few years now. I

Open LLM Leaderboard Evaluation Results

Detailed results can be found here