Instructions to use stillerman/magic-starcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use stillerman/magic-starcoder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder") model = PeftModel.from_pretrained(base_model, "stillerman/magic-starcoder") - Notebooks
- Google Colab
- Kaggle
File size: 993 Bytes
6695e42 | 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 37 38 39 40 | {
"_name_or_path": "bigcode/starcoder",
"activation_function": "gelu",
"architectures": [
"GPTBigCodeForCausalLM"
],
"attention_softmax_in_fp32": true,
"attn_pdrop": 0.1,
"bos_token_id": 0,
"embd_pdrop": 0.1,
"eos_token_id": 0,
"inference_runner": 0,
"initializer_range": 0.02,
"layer_norm_epsilon": 1e-05,
"max_batch_size": null,
"max_sequence_length": null,
"model_type": "gpt_bigcode",
"multi_query": true,
"n_embd": 6144,
"n_head": 48,
"n_inner": 24576,
"n_layer": 40,
"n_positions": 8192,
"pad_key_length": true,
"pre_allocate_kv_cache": false,
"resid_pdrop": 0.1,
"scale_attention_softmax_in_fp32": true,
"scale_attn_weights": true,
"summary_activation": null,
"summary_first_dropout": 0.1,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"torch_dtype": "float32",
"transformers_version": "4.37.0",
"use_cache": false,
"validate_runner_input": true,
"vocab_size": 49152
}
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