license, datasets, language, base_model, tags

license	datasets	language	base_model	tags
llama3.1	OpenCoder-LLM/opc-sft-stage1 OpenCoder-LLM/opc-sft-stage2 microsoft/orca-agentinstruct-1M-v1 microsoft/orca-math-word-problems-200k NousResearch/hermes-function-calling-v1 AI-MO/NuminaMath-CoT AI-MO/NuminaMath-TIR allenai/tulu-3-sft-mixture cognitivecomputations/dolphin-coder HuggingFaceTB/smoltalk cognitivecomputations/samantha-data m-a-p/CodeFeedback-Filtered-Instruction m-a-p/Code-Feedback	en	cognitivecomputations/Dolphin3.0-Llama3.1-8B	mlx

mlx-community/Dolphin3.0-Llama3.1-8B-bf16

The Model mlx-community/Dolphin3.0-Llama3.1-8B-bf16 was converted to MLX format from cognitivecomputations/Dolphin3.0-Llama3.1-8B using mlx-lm version 0.20.5.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Dolphin3.0-Llama3.1-8B-bf16")

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)