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RichardErkhov/
TheBlueObserver_-_Falcon3-1B-Instruct-MLX-gguf

Name: TheBlueObserver_-_Falcon3-1B-Instruct-MLX-gguf
Availability: InStock

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Falcon3-1B-Instruct-MLX - GGUF

Model creator: https://huggingface.co/TheBlueObserver/
Original model: https://huggingface.co/TheBlueObserver/Falcon3-1B-Instruct-MLX/

Name	Quant method	Size
Falcon3-1B-Instruct-MLX.Q2_K.gguf	Q2_K	0.68GB
Falcon3-1B-Instruct-MLX.IQ3_XS.gguf	IQ3_XS	0.75GB
Falcon3-1B-Instruct-MLX.IQ3_S.gguf	IQ3_S	0.77GB
Falcon3-1B-Instruct-MLX.Q3_K_S.gguf	Q3_K_S	0.77GB
Falcon3-1B-Instruct-MLX.IQ3_M.gguf	IQ3_M	0.79GB
Falcon3-1B-Instruct-MLX.Q3_K.gguf	Q3_K	0.82GB
Falcon3-1B-Instruct-MLX.Q3_K_M.gguf	Q3_K_M	0.82GB
Falcon3-1B-Instruct-MLX.Q3_K_L.gguf	Q3_K_L	0.87GB
Falcon3-1B-Instruct-MLX.IQ4_XS.gguf	IQ4_XS	0.91GB
Falcon3-1B-Instruct-MLX.Q4_0.gguf	Q4_0	0.94GB
Falcon3-1B-Instruct-MLX.IQ4_NL.gguf	IQ4_NL	0.95GB
Falcon3-1B-Instruct-MLX.Q4_K_S.gguf	Q4_K_S	0.95GB
Falcon3-1B-Instruct-MLX.Q4_K.gguf	Q4_K	0.98GB
Falcon3-1B-Instruct-MLX.Q4_K_M.gguf	Q4_K_M	0.98GB
Falcon3-1B-Instruct-MLX.Q4_1.gguf	Q4_1	1.03GB
Falcon3-1B-Instruct-MLX.Q5_0.gguf	Q5_0	1.11GB
Falcon3-1B-Instruct-MLX.Q5_K_S.gguf	Q5_K_S	1.11GB
Falcon3-1B-Instruct-MLX.Q5_K.gguf	Q5_K	1.13GB
Falcon3-1B-Instruct-MLX.Q5_K_M.gguf	Q5_K_M	1.13GB
Falcon3-1B-Instruct-MLX.Q5_1.gguf	Q5_1	1.19GB
Falcon3-1B-Instruct-MLX.Q6_K.gguf	Q6_K	1.28GB
Falcon3-1B-Instruct-MLX.Q8_0.gguf	Q8_0	1.66GB

Original model description:

base_model: tiiuae/Falcon3-1B-Instruct language:

en
fr
es
pt library_name: transformers license: other license_name: falcon-llm-license license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html tags:
falcon3
mlx

TheBlueObserver/Falcon3-1B-Instruct-MLX

The Model TheBlueObserver/Falcon3-1B-Instruct-MLX was converted to MLX format from tiiuae/Falcon3-1B-Instruct using mlx-lm version 0.20.2.

Use with mlx

pip install mlx-lm

python

from mlx_lm import load, generate

model, tokenizer = load("TheBlueObserver/Falcon3-1B-Instruct-MLX")

prompt="hello"

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

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

RichardErkhov/TheBlueObserver_-_Falcon3-1B-Instruct-MLX-gguf

Original model description:

TheBlueObserver/Falcon3-1B-Instruct-MLX

Use with mlx

RichardErkhov/
TheBlueObserver_-_Falcon3-1B-Instruct-MLX-gguf