Text Generation
MLX
Safetensors
English
lemonseed
mixture-of-experts
gated-deltanet
mixture-of-depths
rocm
base-model
Instructions to use lemonade-sdk/lemonseed-1.5b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use lemonade-sdk/lemonseed-1.5b-base 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("lemonade-sdk/lemonseed-1.5b-base") 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 lemonade-sdk/lemonseed-1.5b-base with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "lemonade-sdk/lemonseed-1.5b-base" --prompt "Once upon a time"
- Atomic Chat
| { | |
| "vocab_size": 248320, | |
| "hidden_size": 1024, | |
| "num_layers": 20, | |
| "full_attention_interval": 4, | |
| "global_attention_layers": [ | |
| 3, | |
| 7, | |
| 11, | |
| 15, | |
| 19 | |
| ], | |
| "sliding_window": 256, | |
| "attn_q_heads": 16, | |
| "attn_kv_heads": 2, | |
| "attn_head_dim": 64, | |
| "rope_dim": 64, | |
| "rope_theta": 500000.0, | |
| "gdn_qk_heads": 8, | |
| "gdn_v_heads": 4, | |
| "gdn_head_dim": 64, | |
| "gdn_conv_kernel": 4, | |
| "gdn_chunk_size": 32, | |
| "num_experts": 8, | |
| "num_active_experts": 2, | |
| "num_shared_experts": 1, | |
| "expert_intermediate": 2176, | |
| "router_aux_loss_coef": 0.01, | |
| "router_z_loss_coef": 0.001, | |
| "expert_score_band": 0.15, | |
| "use_mod": true, | |
| "mod_top_k": 3, | |
| "mod_threshold": 0.15, | |
| "mod_aux_loss_coef": 0.01, | |
| "train_seq_len": 2048, | |
| "rms_eps": 1e-06, | |
| "dtype": "bfloat16", | |
| "grad_checkpoint_segment": 1 | |
| } |