Upload folder using huggingface_hub

README.md

@@ -13,41 +13,5 @@ Note the model is in float16.
 
 Codes:
 ```python
-import transformers
-import torch
-import os
-from huggingface_hub import create_repo, upload_folder
-
-source_model_id = 'stabilityai/stablelm-2-1_6b'
-save_path = '/tmp/yujiepan/stablelm-2-tiny-random'
-repo_id = 'yujiepan/stablelm-2-tiny-random'
-
-config = transformers.AutoConfig.from_pretrained(
-    source_model_id, trust_remote_code=True)
-config.hidden_size = 4
-config.intermediate_size = 6
-config.num_attention_heads = 4
-config.num_hidden_layers = 2
-config.num_key_value_heads = 2
-config.torch_dtype = torch.float16
-
-model = transformers.AutoModelForCausalLM.from_config(
-    config, trust_remote_code=True, torch_dtype=torch.float16)
-model = model.half()
-print(next(iter(model.parameters())).dtype)
-model.config.torch_dtype = torch.float16
-
-tokenizer = transformers.AutoTokenizer.from_pretrained(
-    source_model_id, trust_remote_code=True)
-
-result = transformers.pipelines.pipeline(
-    'text-generation',
-    model=model.float(), tokenizer=tokenizer)('Hello World!')
-print(result)
-
-model.save_pretrained(save_path)
-tokenizer.save_pretrained(save_path)
-os.system(f'ls -alh {save_path}')
-# create_repo(repo_id, exist_ok=True)
-# upload_folder(repo_id=repo_id, folder_path=save_path)
+model.config
 ```

config.json

@@ -21,7 +21,7 @@
   "rope_scaling": null,
   "rope_theta": 10000,
   "tie_word_embeddings": false,
-  "torch_dtype": "float32",
+  "torch_dtype": "float16",
   "transformers_version": "4.39.0",
   "use_cache": true,
   "use_qkv_bias": true,

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0b31730a65c0a5975358dce3ab7fa6e96aeff6acd6bdcdabf75dc60ada7644a8
-size 3215696
+oid sha256:00257f3077b772910186736a9f5760978bbcfacca5e20ceb6ad6af885294be80
+size 1609472