Instructions to use ekryski/OLMo-2-0425-1B-Instruct-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ekryski/OLMo-2-0425-1B-Instruct-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir OLMo-2-0425-1B-Instruct-4bit ekryski/OLMo-2-0425-1B-Instruct-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 830 Bytes
bb6c241 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"architectures" : [
"Olmo2ForCausalLM"
],
"attention_bias" : 0,
"attention_dropout" : 0,
"eos_token_id" : 100257,
"hidden_act" : "silu",
"hidden_size" : 2048,
"initializer_range" : 0.02,
"intermediate_size" : 8192,
"max_position_embeddings" : 4096,
"model_type" : "olmo2",
"num_attention_heads" : 16,
"num_hidden_layers" : 16,
"num_key_value_heads" : 16,
"pad_token_id" : 100277,
"quantization" : {
"bits" : 4,
"group_size" : 64,
"mode" : "affine"
},
"quantization_config" : {
"bits" : 4,
"group_size" : 64,
"mode" : "affine"
},
"rms_norm_eps" : 9.9999999999999995e-07,
"rope_scaling" : null,
"rope_theta" : 500000,
"tie_word_embeddings" : 0,
"torch_dtype" : "bfloat16",
"transformers_version" : "4.50.0",
"use_cache" : 0,
"vocab_size" : 100352
} |