Update README.md

README.md

@@ -1,57 +1,4 @@
 ---
 library_name: transformers
 pipeline_tag: text-generation
-inference: true
-widget:
-- text: Hello!
-  example_title: Hello world
-  group: Python
 ---
-
-This model is for debugging. It is randomly initialized using the config from [microsoft/Phi-3.5-MoE-instruct](https://huggingface.co/microsoft/Phi-3.5-MoE-instruct) but with smaller size. 
-
-Codes:
-```python
-import os
-
-import torch
-import transformers
-from transformers import (AutoConfig, AutoModelForCausalLM, AutoTokenizer,
-                          GenerationConfig, pipeline, set_seed)
-
-model_id = "microsoft/Phi-3.5-MoE-instruct"
-repo_id = "yujiepan/phi-3.5-moe-tiny-random"
-save_path = f"/tmp/{repo_id}"
-
-config = AutoConfig.from_pretrained(model_id, trust_remote_code=True)
-config.hidden_size = 16
-config.intermediate_size = 32
-config.num_attention_heads = 4
-config.num_hidden_layers = 2
-config.num_key_value_heads = 4
-config.rope_scaling['long_factor'] = [1.0299, 1.0499]
-config.rope_scaling['short_factor'] = [1.05, 1.05]
-
-tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
-tokenizer.save_pretrained(save_path)
-
-model = AutoModelForCausalLM.from_config(
-    config, torch_dtype=torch.bfloat16,
-    # attn_implementation="sdpa",
-    trust_remote_code=True,
-)
-model.generation_config = GenerationConfig.from_pretrained(
-    model_id, trust_remote_code=True
-)
-
-set_seed(42)
-with torch.no_grad():
-    for _, p in sorted(model.named_parameters()):
-        torch.nn.init.uniform_(p, -0.3, 0.3)
-
-model.save_pretrained(save_path)
-
-pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device="cuda",
-                trust_remote_code=True, max_new_tokens=20)
-print(pipe('Hello'))
-```