license, library_name, tags, base_model, model-index

license	library_name	tags	base_model	model-index
apache-2.0	transformers	mergekit merge	mistralai/Mistral-7B-Instruct-v0.2	name results bigstral-12b-32k 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 41.94 strict accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/bigstral-12b-32k 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 25.56 normalized accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/bigstral-12b-32k 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 0.98 exact match url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/bigstral-12b-32k 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 5.7 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/bigstral-12b-32k 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 15.86 acc_norm url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/bigstral-12b-32k 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 18.24 accuracy url name https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=abacusai/bigstral-12b-32k Open LLM Leaderboard

bigstral-12b-32k

ollama run ehartford/bigstral

I reached for SOLAR but realized that its only 4k... Decided to make my own 32k version.

This is mistralai/Mistral-7B-Instruct-v0.2 with layers interleaved to create a larger 12b model.

This is a merge of pre-trained language models created using mergekit.

Prompt Format

<s>[INST] What is your favourite condiment? [/INST]
Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!</s>
[INST] Do you have dangerously spicy mayonnaise recipes? [/INST]

Example Output

give me some code that is very simple in javascript but would be very difficult in ANSI-C

In JavaScript, functions are first-class values, which means you can assign them to variables, pass them as arguments to other functions, and even nest them inside other functions. This leads to concise and expressive code.

Here's an example of a simple recursive function that calculates the factorial of a given number in JavaScript:

const factorial = n => n === 0 ? 1 : n * factorial(n - 1);

console.log(factorial(5)); // Output: 120

Now, let's try to write an equivalent code snippet in ANSI-C with similar functionality:

#include <stdio.h>
#define MAX_RECURSION_DEPTH 1000
int factorial(int n) {
    if (n == 0)
        return 1;
    else {
        int result;
        result = factorial(--n);
        if (++depth > MAX_RECURSION_DEPTH)
            while(1){} // Recursion stack overflow
        return n * result;
    }
}
int main() {
    int i, result;
    int n = 5;
    int depth = 0;

    result = factorial(n);
    printf("Factorial of %d is: %d\n", n, result);
    return 0;
}

As you can see, the ANSI-C code becomes more verbose and has several disadvantages compared to JavaScript:

1. Need to define a maximum recursion depth using a constant or an array index, which can lead to hardcoded limits and potential stack overflow issues.
2. The use of preprocessor directives (#define) for defining functions and macros can make the code less readable and harder to understand.
3. The lack of closures in ANSI-C requires using static variables or passing arguments as arguments to nested functions, making the code more verbose and less concise.

Merge Details

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

• mistralai/Mistral-7B-Instruct-v0.2

Configuration

The following YAML configuration was used to produce this model:

dtype: float16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 8]
    model: mistralai/Mistral-7B-Instruct-v0.2
- sources:
  - layer_range: [4, 12]
    model: mistralai/Mistral-7B-Instruct-v0.2
- sources:
  - layer_range: [8, 16]
    model: mistralai/Mistral-7B-Instruct-v0.2
- sources:
  - layer_range: [12, 20]
    model: mistralai/Mistral-7B-Instruct-v0.2
- sources:
  - layer_range: [16, 24]
    model: mistralai/Mistral-7B-Instruct-v0.2
- sources:
  - layer_range: [20, 28]
    model: mistralai/Mistral-7B-Instruct-v0.2
- sources:
  - layer_range: [24, 32]
    model: mistralai/Mistral-7B-Instruct-v0.2

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	18.05
IFEval (0-Shot)	41.94
BBH (3-Shot)	25.56
MATH Lvl 5 (4-Shot)	0.98
GPQA (0-shot)	5.70
MuSR (0-shot)	15.86
MMLU-PRO (5-shot)	18.24