Instructions to use rayonlabs/starcoder2-3b-python_code_instructions_18k_alpaca-3596ac75-01d7-4fdc-bd41-e88e6854c856 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rayonlabs/starcoder2-3b-python_code_instructions_18k_alpaca-3596ac75-01d7-4fdc-bd41-e88e6854c856 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder2-3b") model = PeftModel.from_pretrained(base_model, "rayonlabs/starcoder2-3b-python_code_instructions_18k_alpaca-3596ac75-01d7-4fdc-bd41-e88e6854c856") - Notebooks
- Google Colab
- Kaggle
File size: 804 Bytes
71c5322 | 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 | {
"_attn_implementation_autoset": true,
"_name_or_path": "bigcode/starcoder2-3b",
"architectures": [
"Starcoder2ForCausalLM"
],
"attention_dropout": 0.1,
"bos_token_id": 0,
"embedding_dropout": 0.1,
"eos_token_id": 0,
"hidden_act": "gelu_pytorch_tanh",
"hidden_size": 3072,
"initializer_range": 0.018042,
"intermediate_size": 12288,
"max_position_embeddings": 16384,
"mlp_type": "default",
"model_type": "starcoder2",
"norm_epsilon": 1e-05,
"norm_type": "layer_norm",
"num_attention_heads": 24,
"num_hidden_layers": 30,
"num_key_value_heads": 2,
"residual_dropout": 0.1,
"rope_scaling": null,
"rope_theta": 999999.4420358813,
"sliding_window": 4096,
"transformers_version": "4.46.0",
"use_bias": true,
"use_cache": false,
"vocab_size": 49152
}
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