Instructions to use emese-tech/csermely-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use emese-tech/csermely-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("emese-tech/csermely-mlx") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use emese-tech/csermely-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "emese-tech/csermely-mlx" --prompt "Once upon a time"
File size: 443 Bytes
f2855e3 eef36ff f2855e3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"model_type": "llama",
"vocab_size": 32000,
"d_model": 768,
"n_layers": 16,
"n_heads": 12,
"d_ff": 2048,
"max_seq_len": 2048,
"rope_theta": 10000.0,
"rope_yarn": true,
"rope_yarn_scale": 4.0,
"rope_yarn_alpha": 1.0,
"rope_yarn_beta": 32.0,
"rms_norm_eps": 1e-5,
"tie_word_embeddings": true,
"torch_dtype": "bfloat16",
"repetition_penalty": 1.2,
"bos_token_id": 2,
"eos_token_id": 3,
"pad_token_id": 1
}
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