Delete .ipynb_checkpoints

.ipynb_checkpoints/config-checkpoint.json

@@ -1,29 +0,0 @@
-{
-  "architectures": [
-    "LlamaForCausalLM"
-  ],
-  "attention_bias": false,
-  "attention_dropout": 0.0,
-  "bos_token_id": 1,
-  "eos_token_id": 2,
-  "head_dim": 128,
-  "hidden_act": "silu",
-  "hidden_size": 8192,
-  "initializer_range": 0.02,
-  "intermediate_size": 28672,
-  "max_position_embeddings": 4096,
-  "mlp_bias": false,
-  "model_type": "llama",
-  "num_attention_heads": 64,
-  "num_hidden_layers": 80,
-  "num_key_value_heads": 8,
-  "pretraining_tp": 1,
-  "rms_norm_eps": 1e-05,
-  "rope_scaling": null,
-  "rope_theta": 10000,
-  "tie_word_embeddings": false,
-  "torch_dtype": "float16",
-  "transformers_version": "4.55.0",
-  "use_cache": true,
-  "vocab_size": 32016
-}

.ipynb_checkpoints/upload-checkpoint.py

@@ -1,17 +0,0 @@
-from huggingface_hub import HfApi
-from concurrent.futures import ThreadPoolExecutor
-import os
-
-api = HfApi()
-files = [f"model-000{i:02d}-of-00029.safetensors" for i in range(7, 30)]
-
-def upload_file(filepath):
-    return api.upload_file(
-        path_or_fileobj=filepath,
-        path_in_repo=filepath,
-        repo_id="emissary-ai/Python-Tab-Completion-CodeLlama-70b",
-        repo_type="model"
-    )
-
-with ThreadPoolExecutor(max_workers=50) as executor:
-    executor.map(upload_file, files)