Nbardy commited on
Commit
1de83e7
1 Parent(s): fcb62c1
README.md CHANGED
@@ -1,5 +1,18 @@
1
- TODO: Complete
2
 
3
- This architecture takes GQA and tied embeddings to create an effeceint 5B model
4
 
5
- This uses a mix of data yet to be published
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ### Micro Mistral
2
 
3
+ This is a small mistral model with 6 layers
4
 
5
+ It is similar to smol llama varaints uses GQA and tied embeddings.
6
+ Except it uses mistral style arch with GQA and sliding window attention
7
+
8
+ This architecture takes GQA and tied embeddings to create an effeceint 0.5B model that uses the mistral architecture(It is supported in downstream applications)
9
+
10
+ #### Dataset
11
+
12
+ Minipile
13
+ Instruct
14
+ Math
15
+ OpenOrca
16
+ Synthetic Data
17
+
18
+ TODO: Complete Dataset section
config.json CHANGED
@@ -25,6 +25,5 @@
25
  "torch_dtype": "bfloat16",
26
  "transformers_version": "4.34.1",
27
  "use_cache": true,
28
- "vocab_size": 50304,
29
-
30
- }
 
25
  "torch_dtype": "bfloat16",
26
  "transformers_version": "4.34.1",
27
  "use_cache": true,
28
+ "vocab_size": 50304
29
+ }
 
init_model.py ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import torch
2
+ from transformers import AutoConfig, AutoModelForCausalLM
3
+
4
+ # Load the configuration and initialize the model
5
+ config_path = "config.json" # Adjust path as necessary
6
+ config = AutoConfig.from_pretrained(config_path)
7
+ model = AutoModelForCausalLM.from_config(config)
8
+
9
+
10
+ # Reinitialize weights with a standard deviation of 0.02 for a more controlled initialization
11
+ def reinitialize_weights(module):
12
+ if hasattr(module, "weight") and not isinstance(module, torch.nn.LayerNorm):
13
+ torch.nn.init.normal_(module.weight, mean=0.0, std=0.02)
14
+ if hasattr(module, "bias") and module.bias is not None:
15
+ torch.nn.init.constant_(module.bias, 0.0)
16
+
17
+
18
+ model.apply(reinitialize_weights)
19
+
20
+ # Cast the model's parameters to bf16
21
+ model = model.to(
22
+ dtype=torch.bfloat16
23
+ ) # Converts all floating point parameters to bfloat16
24
+
25
+ # Save the model with SafeTensors
26
+ model.save_pretrained("./model_bf16.safetensors", save_in_safe_tensors_format=True)
model_bf16.safetensors/config.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "config.json",
3
+ "architectures": [
4
+ "LlamaForCausalLM"
5
+ ],
6
+ "attention_bias": false,
7
+ "attention_dropout": 0.0,
8
+ "bos_token_id": 1,
9
+ "dropout_p": 0.1,
10
+ "eos_token_id": 2,
11
+ "hidden_act": "silu",
12
+ "hidden_size": 1024,
13
+ "initializer_range": 0.02,
14
+ "intermediate_size": 3072,
15
+ "max_position_embeddings": 4096,
16
+ "model_type": "llama",
17
+ "num_attention_heads": 128,
18
+ "num_hidden_layers": 6,
19
+ "num_key_value_heads": 16,
20
+ "pretraining_tp": 1,
21
+ "rms_norm_eps": 1e-05,
22
+ "rope_scaling": null,
23
+ "rope_theta": 10000.0,
24
+ "sliding_window": 1024,
25
+ "tie_word_embeddings": true,
26
+ "torch_dtype": "bfloat16",
27
+ "transformers_version": "4.36.2",
28
+ "use_cache": true,
29
+ "vocab_size": 50304
30
+ }
model_bf16.safetensors/generation_config.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 1,
4
+ "eos_token_id": 2,
5
+ "transformers_version": "4.36.2"
6
+ }