Nondzu commited on
Commit
0556e02
1 Parent(s): 90a6e75

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +93 -0
README.md CHANGED
@@ -1,3 +1,96 @@
1
  ---
2
  license: apache-2.0
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
  license: apache-2.0
3
+ tags:
4
+ - code
5
+ - mistral
6
  ---
7
+
8
+ # Mistral-7B-codealpaca
9
+
10
+ We are thrilled to introduce the Mistral-7B-codealpaca-test14 model. This variant is optimized and demonstrates potential in assisting developers as a coding companion. We welcome contributions from testers and enthusiasts to help evaluate its performance.
11
+
12
+ ## Training Details
13
+
14
+ The model was trained using 3xRTX 3090 in a homelab setup.
15
+ [![Built with Axolotl](https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png)](https://github.com/OpenAccess-AI-Collective/axolotl)
16
+
17
+
18
+ ## Quantised Model Links:
19
+
20
+ 1.
21
+ 2.
22
+ 3.
23
+
24
+ ## Dataset:
25
+
26
+ - Dataset Name: theblackcat102/evol-codealpaca-v1
27
+ - Dataset Link: [theblackcat102/evol-codealpaca-v1](https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1)
28
+
29
+ ## Prompt template: Alpaca
30
+
31
+ ```
32
+ Below is an instruction that describes a task. Write a response that appropriately completes the request.
33
+
34
+ ### Instruction:
35
+ {prompt}
36
+
37
+ ### Response:
38
+
39
+ ```
40
+
41
+
42
+ ## Performance (evalplus)
43
+
44
+ ### The results from evalplus for the Mistral-7B-codealpaca are still pending.
45
+
46
+ For reference, we've provided the performance of the original Mistral model alongside Mistral-7B-code-16k-qlora model.
47
+
48
+ ** [Nondzu/Mistral-7B-code-16k-qlora](https://huggingface.co/Nondzu/Mistral-7B-code-16k-qlora)**:
49
+
50
+ - Base: `{'pass@1': 0.3353658536585366}`
51
+ - Base + Extra: `{'pass@1': 0.2804878048780488}`
52
+
53
+ ** [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)**:
54
+
55
+ - Base: `{'pass@1': 0.2926829268292683}`
56
+ - Base + Extra: `{'pass@1': 0.24390243902439024}`
57
+
58
+ ## Model Configuration:
59
+
60
+ The following are the configurations for the Mistral-7B-codealpaca-lora:
61
+
62
+ ```yaml
63
+ base_model: mistralai/Mistral-7B-Instruct-v0.1
64
+ base_model_config: mistralai/Mistral-7B-Instruct-v0.1
65
+ model_type: MistralForCausalLM
66
+ tokenizer_type: LlamaTokenizer
67
+ is_mistral_derived_model: true
68
+ load_in_8bit: true
69
+ load_in_4bit: false
70
+ strict: false
71
+ datasets:
72
+ - path: theblackcat102/evol-codealpaca-v1
73
+ type: oasst
74
+ dataset_prepared_path:
75
+ val_set_size: 0.01
76
+ output_dir: ./nondzu/Mistral-7B-codealpaca-test14
77
+ adapter: lora
78
+ sequence_len: 4096
79
+ sample_packing: true
80
+ pad_to_sequence_len: true
81
+ lora_r: 32
82
+ lora_alpha: 16
83
+ lora_dropout: 0.05
84
+ lora_target_modules:
85
+ lora_target_linear: true
86
+ ```
87
+
88
+
89
+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63729f35acef705233c87909/5nPgL3ajROKf7dttf4BO0.png)
90
+
91
+
92
+ ## Additional Projects:
93
+
94
+ For other related projects, you can check out:
95
+
96
+ - [LlamaTor on GitHub](https://github.com/Nondzu/LlamaTor)