license, base_model, datasets, inference, widget, model-index

license	base_model	datasets	inference	widget	model-index
apache-2.0	BEE-spoke-data/smol_llama-220M-GQA	teknium/openhermes	parameters do_sample renormalize_logits temperature top_p top_k min_new_tokens max_new_tokens repetition_penalty no_repeat_ngram_size epsilon_cutoff true true 0.25 0.95 50 2 96 1.03 5 0.0008	text example_title Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: Write an ode to Chipotle burritos. ### Response: burritos	name results smol_llama-220M-openhermes task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 25.17 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 28.98 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 26.17 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 43.08 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 52.01 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 0.61 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args IFEval (0-Shot) HuggingFaceH4/ifeval num_few_shot 0 type value name inst_level_strict_acc and prompt_level_strict_acc 15.55 strict accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args BBH (3-Shot) BBH num_few_shot 3 type value name acc_norm 3.11 normalized accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args MATH Lvl 5 (4-Shot) hendrycks/competition_math num_few_shot 4 type value name exact_match 0.0 exact match url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args GPQA (0-shot) Idavidrein/gpqa num_few_shot 0 type value name acc_norm 2.35 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type args MuSR (0-shot) TAUR-Lab/MuSR num_few_shot 0 type value name acc_norm 6.22 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU-PRO (5-shot) TIGER-Lab/MMLU-Pro main test num_few_shot 5 type value name acc 1.34 accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-openhermes Open LLM Leaderboard

BEE-spoke-data/smol_llama-220M-openhermes

Please note that this is an experiment, and the model has limitations because it is smol.

prompt format is alpaca

Below is an instruction that describes a task, paired with an input that
provides further context. Write a response that appropriately completes
the request.  

### Instruction:  

How can I increase my meme production/output? Currently, I only create them in ancient babylonian which is time consuming.  

### Inputs:

### Response:

It was trained on inputs so if you have inputs (like some text to ask a question about) then include it under ### Inputs:

Example

Output on the text above ^. The inference API is set to sample with low temp so you should see (at least slightly) different generations each time.

Note that the inference API parameters used here are an initial educated guess, and may be updated over time:

inference:
  parameters:
    do_sample: true
    renormalize_logits: true
    temperature: 0.25
    top_p: 0.95
    top_k: 50
    min_new_tokens: 2
    max_new_tokens: 96
    repetition_penalty: 1.03
    no_repeat_ngram_size: 5
    epsilon_cutoff: 0.0008

Feel free to experiment with the parameters using the model in Python and let us know if you have improved results with other params!

Data

Note that this checkpoint was fine-tuned on teknium/openhermes, which is generated/synthetic data by an OpenAI model. This means usage of this checkpoint should follow their terms of use: https://openai.com/policies/terms-of-use

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Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	29.34
AI2 Reasoning Challenge (25-Shot)	25.17
HellaSwag (10-Shot)	28.98
MMLU (5-Shot)	26.17
TruthfulQA (0-shot)	43.08
Winogrande (5-shot)	52.01
GSM8k (5-shot)	0.61

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	4.76
IFEval (0-Shot)	15.55
BBH (3-Shot)	3.11
MATH Lvl 5 (4-Shot)	0.00
GPQA (0-shot)	2.35
MuSR (0-shot)	6.22
MMLU-PRO (5-shot)	1.34