Text Generation
MLX
Safetensors
Hungarian
llama
hungarian
emese
from-scratch
base-model
apple-silicon
quantized
8-bit precision
Instructions to use emese-tech/er-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use emese-tech/er-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/er-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/er-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/er-mlx" --prompt "Once upon a time"
- Atomic Chat
Download config.json from emese-tech/er-mlx: direct link, hf CLI and curl.
- Browser
- Download file 896 Bytes
-
https://huggingface.co/emese-tech/er-mlx/resolve/main/config.json
- Command line
-
hf download hf://emese-tech/er-mlx/config.json
-
curl -L -o config.json https://huggingface.co/emese-tech/er-mlx/resolve/main/config.json
896 Bytes
| { | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "bos_token_id": 2, | |
| "eos_token_id": 3, | |
| "hidden_act": "silu", | |
| "hidden_size": 1280, | |
| "intermediate_size": 3456, | |
| "max_position_embeddings": 32768, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 20, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 20, | |
| "pad_token_id": 1, | |
| "quantization": { | |
| "group_size": 64, | |
| "bits": 8, | |
| "mode": "affine" | |
| }, | |
| "quantization_config": { | |
| "group_size": 64, | |
| "bits": 8, | |
| "mode": "affine" | |
| }, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": { | |
| "rope_type": "yarn", | |
| "factor": 4.0, | |
| "original_max_position_embeddings": 8192 | |
| }, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": true, | |
| "torch_dtype": "bfloat16", | |
| "vocab_size": 32000 | |
| } |