Piccolo MoE
Collection
MoEs skilled in math and programming. This is experimentation of my daily driver.
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6 items
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Updated
In loving memory of my dog Klaus (Piccolo)
~ Piccolo (Italian): the little one ~
Quants are available here
Inference and Evaluation colab available here
from transformers import AutoModelForCausalLM, AutoTokenizer
def generate_response(prompt):
"""
Generate a response from the model based on the input prompt.
Args:
prompt (str): Prompt for the model.
Returns:
str: The generated response from the model.
"""
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256, eos_token_id=tokenizer.eos_token_id, pad_token_id=tokenizer.pad_token_id)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return response
model_id = "macadeliccc/piccolo-2x7b"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id,load_in_4bit=True)
prompt = "What is the best way to train Cane Corsos?"
print("Response:")
print(generate_response(prompt), "\n")
The model is capable of quality code, math, and logical reasoning. Try whatever questions you think of.
Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
---|---|---|---|---|---|---|---|
arc_easy | Yaml | none | 0 | acc | 0.8552 | ± | 0.0072 |
none | 0 | acc_norm | 0.8237 | ± | 0.0078 | ||
boolq | Yaml | none | 0 | acc | 0.8749 | ± | 0.0058 |
hellaswag | Yaml | none | 0 | acc | 0.6734 | ± | 0.0047 |
none | 0 | acc_norm | 0.8489 | ± | 0.0036 | ||
openbookqa | Yaml | none | 0 | acc | 0.3640 | ± | 0.0215 |
none | 0 | acc_norm | 0.4780 | ± | 0.0224 | ||
piqa | Yaml | none | 0 | acc | 0.8330 | ± | 0.0087 |
none | 0 | acc_norm | 0.8368 | ± | 0.0086 | ||
winogrande | Yaml | none | 0 | acc | 0.7703 | ± | 0.0118 |
Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
---|---|---|---|---|---|
piccolo-math-2x7b | 43.89% | 74.98% | 63.96% | 44.99% | 56.96% |
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
agieval_aqua_rat | 0 | acc | 24.41 | ± 2.70 |
acc_norm | 24.80 | ± 2.72 | ||
agieval_logiqa_en | 0 | acc | 35.79 | ± 1.88 |
acc_norm | 36.71 | ± 1.89 | ||
agieval_lsat_ar | 0 | acc | 23.48 | ± 2.80 |
acc_norm | 23.91 | ± 2.82 | ||
agieval_lsat_lr | 0 | acc | 49.22 | ± 2.22 |
acc_norm | 50.00 | ± 2.22 | ||
agieval_lsat_rc | 0 | acc | 63.94 | ± 2.93 |
acc_norm | 64.31 | ± 2.93 | ||
agieval_sat_en | 0 | acc | 77.18 | ± 2.93 |
acc_norm | 76.70 | ± 2.95 | ||
agieval_sat_en_without_passage | 0 | acc | 45.15 | ± 3.48 |
acc_norm | 44.66 | ± 3.47 | ||
agieval_sat_math | 0 | acc | 33.64 | ± 3.19 |
acc_norm | 30.00 | ± 3.10 |
Average: 43.89%
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
arc_challenge | 0 | acc | 61.86 | ± 1.42 |
acc_norm | 62.88 | ± 1.41 | ||
arc_easy | 0 | acc | 84.34 | ± 0.75 |
acc_norm | 80.47 | ± 0.81 | ||
boolq | 1 | acc | 86.88 | ± 0.59 |
hellaswag | 0 | acc | 68.56 | ± 0.46 |
acc_norm | 85.16 | ± 0.35 | ||
openbookqa | 0 | acc | 37.00 | ± 2.16 |
acc_norm | 47.80 | ± 2.24 | ||
piqa | 0 | acc | 82.21 | ± 0.89 |
acc_norm | 83.68 | ± 0.86 | ||
winogrande | 0 | acc | 77.98 | ± 1.16 |
Average: 74.98%
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
truthfulqa_mc | 1 | mc1 | 47.37 | ± 1.75 |
mc2 | 63.96 | ± 1.57 |
Average: 63.96%
Task | Version | Metric | Value | Stderr |
---|---|---|---|---|
bigbench_causal_judgement | 0 | multiple_choice_grade | 55.26 | ± 3.62 |
bigbench_date_understanding | 0 | multiple_choice_grade | 63.14 | ± 2.51 |
bigbench_disambiguation_qa | 0 | multiple_choice_grade | 42.64 | ± 3.08 |
bigbench_geometric_shapes | 0 | multiple_choice_grade | 22.84 | ± 2.22 |
exact_str_match | 3.34 | ± 0.95 | ||
bigbench_logical_deduction_five_objects | 0 | multiple_choice_grade | 36.60 | ± 2.16 |
bigbench_logical_deduction_seven_objects | 0 | multiple_choice_grade | 25.57 | ± 1.65 |
bigbench_logical_deduction_three_objects | 0 | multiple_choice_grade | 56.00 | ± 2.87 |
bigbench_movie_recommendation | 0 | multiple_choice_grade | 42.40 | ± 2.21 |
bigbench_navigate | 0 | multiple_choice_grade | 54.70 | ± 1.57 |
bigbench_reasoning_about_colored_objects | 0 | multiple_choice_grade | 62.90 | ± 1.08 |
bigbench_ruin_names | 0 | multiple_choice_grade | 53.35 | ± 2.36 |
bigbench_salient_translation_error_detection | 0 | multiple_choice_grade | 24.35 | ± 1.36 |
bigbench_snarks | 0 | multiple_choice_grade | 62.43 | ± 3.61 |
bigbench_sports_understanding | 0 | multiple_choice_grade | 70.28 | ± 1.46 |
bigbench_temporal_sequences | 0 | multiple_choice_grade | 41.30 | ± 1.56 |
bigbench_tracking_shuffled_objects_five_objects | 0 | multiple_choice_grade | 22.32 | ± 1.18 |
bigbench_tracking_shuffled_objects_seven_objects | 0 | multiple_choice_grade | 17.77 | ± 0.91 |
bigbench_tracking_shuffled_objects_three_objects | 0 | multiple_choice_grade | 56.00 | ± 2.87 |
Average score: 56.96%