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🔥 DeepSeek R1 (0528) — компактная MLX-версия!

А вот и 4-битная квантованная версия DeepSeek R1 специально под MLX.

Модель запускается локально на Mac с Apple Silicon без танцев с бубном и GPU.

Установка:

pip install mlx-lm


from mlx_lm import load, generate

model, tokenizer = load("mlx-community/DeepSeek-R1-0528-4bit")

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)


👉 huggingface.co/mlx-community/DeepSeek-R1-0528-4bit

#DeepSeek



tg-me.com/machinelearning_interview/1820
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🔥 DeepSeek R1 (0528) — компактная MLX-версия!

А вот и 4-битная квантованная версия DeepSeek R1 специально под MLX.

Модель запускается локально на Mac с Apple Silicon без танцев с бубном и GPU.

Установка:

pip install mlx-lm


from mlx_lm import load, generate

model, tokenizer = load("mlx-community/DeepSeek-R1-0528-4bit")

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)


👉 huggingface.co/mlx-community/DeepSeek-R1-0528-4bit

#DeepSeek

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A Telegram spokesman declined to comment on the bond issue or the amount of the debt the company has due. The spokesman said Telegram’s equipment and bandwidth costs are growing because it has consistently posted more than 40% year-to-year growth in users.

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