Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx

Name: Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx
Author: nightmedia

130

3 languages

—

nightmedia

Language Model

OTHER

22B params

New

130 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

50GB+ RAM

Mobile

Laptop

Server

Quick Summary

Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx This model Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx was converted to MLX format from DavidAU...

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

21GB+ RAM

Code Examples

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxbash

pip install mlx-lm

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

Use with mlxpython

from mlx_lm import load, generate

model, tokenizer = load("Mistral-2x22B-MOE-Power-Codestral-Ultimate-39B-q8-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

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