Text Generation
MLX
Safetensors
Hungarian
llama
hungarian
emese
from-scratch
base-model
apple-silicon
Instructions to use emese-tech/er with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use emese-tech/er 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/er") 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/er 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/er" --prompt "Once upon a time"
- Atomic Chat
File size: 392 Bytes
479bc24 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"model_type": "llama",
"vocab_size": 32000,
"d_model": 1280,
"n_layers": 24,
"n_heads": 20,
"d_ff": 3456,
"max_seq_len": 8192,
"rope_theta": 10000.0,
"rope_yarn": true,
"rope_yarn_scale": 4.0,
"rms_norm_eps": 1e-6,
"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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