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config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "eos_token_id": [
+    200002
+  ],
+  "hidden_act": "silu",
+  "hidden_size": 2880,
+  "initializer_range": 0.02,
+  "head_dim":64,
+  "intermediate_size": 10080,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 1,
+  "num_key_value_heads": 8,
+  "pad_token_id": 199999,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "low_freq_factor": 1.0,
+    "high_freq_factor": 4.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.42.3",
+  "use_cache": true,
+  "draft_vocab_size": 201088,
+  "vocab_size": 201088
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:518ccc5fe9917ccd65253b7c18bd2634943b3bd7790a54948e2769aae7981de8
+size 2624892360

print.py

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+from safetensors.torch import safe_open
+
+file=safe_open("model.safetensors", 'pt')
+print(file.keys())
+f=file
+for k in f.keys():
+    t = f.get_tensor(k)          # torch.Tensor
+    print(f"{k}: shape={tuple(t.shape)} dtype={t.dtype}")