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leafspark/
Mistral-Large-218B-Instruct

Name: Mistral-Large-218B-Instruct
Rating: 2.5 (67 reviews)

text-generation-inference

endpoints_compatible

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Mistral-Large-218B-Instruct

Mistral-Large-218B-Instruct is a dense Large Language Model (LLM) with 218 billion parameters. Self-merged from the original Mistral Large 2.

Key features

218 billion parameters
Multi-lingual support for dozens of languages
Trained on 80+ coding languages
128k context window
Mistral Research License: Allows usage and modification for research and non-commercial purposes

Hardware Requirements

Given the size of this model (218B parameters), it requires substantial computational resources for inference:

Recommended: 8xH100 (640GB)
Alternatively: Distributed inference setup across multiple machines

Limitations

No built-in moderation mechanisms
Computationally expensive inference
May exhibit biases present in training data
Outputs should be critically evaluated for sensitive applications

Notes

This was just a fun testing model, merged with the merge.py script in the base of the repo.

Quants

GGUF: mradermacher/Mistral-Large-218B-Instruct-GGUF

imatrix GGUF: mradermacher/Mistral-Large-218B-Instruct-i1-GGUF

Compatible mergekit config:

yaml

slices:
- sources:
  - layer_range: [0, 20]
    model: mistralai/Mistral-Large-Instruct-2407
- sources:
  - layer_range: [10, 30]
    model: mistralai/Mistral-Large-Instruct-2407
- sources:
  - layer_range: [20, 40]
    model: mistralai/Mistral-Large-Instruct-2407
- sources:
  - layer_range: [30, 50]
    model: mistralai/Mistral-Large-Instruct-2407
- sources:
  - layer_range: [40, 60]
    model: mistralai/Mistral-Large-Instruct-2407
- sources:
  - layer_range: [50, 70]
    model: mistralai/Mistral-Large-Instruct-2407
- sources:
  - layer_range: [60, 80]
    model: mistralai/Mistral-Large-Instruct-2407
- sources:
  - layer_range: [70, 87]
    model: mistralai/Mistral-Large-Instruct-2407
merge_method: passthrough
dtype: bfloat16

leafspark/Mistral-Large-218B-Instruct