mergekit-dare_ties-nlzuacx

Name: mergekit-dare_ties-nlzuacx
Author: mergekit-community

llama

mergekit-community

Language Model

OTHER

2306.01708B params

New

1 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

5155GB+ RAM

Mobile

Laptop

Server

Quick Summary

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

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

2148GB+ RAM

Code Examples

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Configurationyaml

models:
  - model: nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
    parameters:
      density: [0.00, 0.00, 0.15, 0.75, 1.00]
      weight: [0.00, 0.00, 0.15, 0.75, 0.90]
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
    parameters:
      density: [0.00, 0.00, 1.00, 0.50, 0.00]
      weight: [0.00, 0.00, 0.75, 0.35, 0.00]
merge_method: dare_ties
base_model: unsloth/Llama-3.3-70B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16

Deploy This Model

Production-ready deployment in minutes

Together.ai

Instant API access to this model

Fastest API

Production-ready inference API. Start free, scale to millions.

Try Free API

Replicate

One-click model deployment

Easiest Setup

Run models in the cloud with simple API. No DevOps required.

Deploy Now

Disclosure: We may earn a commission from these partners. This helps keep LLMYourWay free.