xLAM-7b-fc-r/README.md

base_model, datasets, language, license, pipeline_tag, tags, extra_gated_heading, extra_gated_button_content, extra_gated_fields

base_model	datasets	language	license	pipeline_tag	tags	extra_gated_heading	extra_gated_button_content	extra_gated_fields
Salesforce/xLAM-7b-fc-r	Salesforce/xlam-function-calling-60k	en	cc-by-nc-4.0	text-generation	function-calling LLM Agent tool-use deepseek pytorch mlx	Acknowledge to follow corresponding license to access the repository	Agree and access repository	First Name Last Name Country Affiliation text text country text

mlx-community/xLAM-7b-fc-r

The Model mlx-community /xLAM-7b-fc-r was converted to MLX format from Salesforce/xLAM-7b-fc-r using mlx-lm version 0.19.1.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/xLAM-7b-fc-r")

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)