KeeeeepGoing commited on
Commit
bb2fed0
1 Parent(s): c5777e3

Upload 7 files

Browse files
README.md CHANGED
@@ -1,3 +1,50 @@
1
- ---
2
- license: cc-by-nc-sa-4.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-nc-sa-4.0
3
+ widget:
4
+ - text: AGTCGCCGCAACCCACACACGGACGGCTCGACGTGGCGATCTTAGCGGCTCATCCGCCCGGCCTCCCTCGCGCTCGATCGCTACGCAGCCTACGCTCGTTTCGCTCGGTTCGGTGGGTCGCCGATCTGGCGCCACGGCGGCTACCAACGACACCGCGATTGAGAAGGGTGCGTGGCCGTGGAGTCGTGGAGAAACGCCCGCGCGCGCGGGTGCGGCGAGGGACGACGACCGCGTCGTGCGGATCGATTGGCGGGGCAGCTCGGCGCCCCG
5
+ tags:
6
+ - DNA
7
+ - biology
8
+ - genomics
9
+ ---
10
+ # Plant foundation DNA large language models
11
+
12
+ The plant DNA large language models (LLMs) contain a series of foundation models based on different model architectures, which are pre-trained on various plant reference genomes.
13
+ All the models have a comparable model size between 90 MB and 150 MB, BPE tokenizer is used for tokenization and 8000 tokens are included in the vocabulary.
14
+
15
+
16
+ **Developed by:** zhangtaolab
17
+
18
+ ### Model Sources
19
+
20
+ - **Repository:** [Plant DNA LLMs](https://github.com/zhangtaolab/plant_DNA_LLMs)
21
+ - **Manuscript:** [Versatile applications of foundation DNA language models in plant genomes]()
22
+
23
+ ### Architecture
24
+
25
+ The model is trained based on the State-Space Mamba-130m model with modified tokenizer specific for DNA sequence.
26
+
27
+ This model is fine-tuned for predicting H3K27ac histone modification.
28
+
29
+
30
+ ### How to use
31
+
32
+ Install the runtime library first:
33
+ ```bash
34
+ pip install transformers
35
+ pip install causal-conv1d<=1.2.0
36
+ pip install mamba-ssm<2.0.0
37
+ ```
38
+
39
+ Since `transformers` library (version < 4.43.0) does not provide a MambaForSequenceClassification function, we wrote a script to train Mamba model for sequence classification.
40
+ An inference code can be found in our [GitHub](https://github.com/zhangtaolab/plant_DNA_LLMs).
41
+ Note that Plant DNAMamba model requires NVIDIA GPU to run.
42
+
43
+
44
+ ### Training data
45
+ We use a custom MambaForSequenceClassification script to fine-tune the model.
46
+ Detailed training procedure can be found in our manuscript.
47
+
48
+
49
+ #### Hardware
50
+ Model was trained on a NVIDIA GTX4090 GPU (24 GB).
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"d_model": 768, "n_layer": 24, "vocab_size": 75, "ssm_cfg": {}, "rms_norm": true, "residual_in_fp32": true, "fused_add_norm": true, "pad_vocab_size_multiple": 1, "tie_embeddings": true}
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c52b82b6ae2c45c82a3222135b834e817d500315be3100a5d52256f01ea44535
3
+ size 362410522
special_tokens_map.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cls_token": {
3
+ "content": "<cls>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "mask_token": {
10
+ "content": "<mask>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": {
17
+ "content": "<pad>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "unk_token": {
24
+ "content": "<unk>",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ }
30
+ }
test_metrics.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {'test_loss': 0.4393389821052551, 'test_accuracy': 0.79736328125, 'test_f1': 0.8010355738805255, 'test_precision': 0.7867771708419665, 'test_recall': 0.8158203125, 'test_matthews_correlation': 0.5951321785645645, 'test_runtime': 32.108, 'test_samples_per_second': 318.923, 'test_steps_per_second': 19.933}
tokenizer_config.json ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "<unk>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "1": {
12
+ "content": "<pad>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "2": {
20
+ "content": "<mask>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "3": {
28
+ "content": "<cls>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ }
35
+ },
36
+ "clean_up_tokenization_spaces": true,
37
+ "cls_token": "<cls>",
38
+ "eos_token": null,
39
+ "mask_token": "<mask>",
40
+ "model_max_length": 512,
41
+ "pad_token": "<pad>",
42
+ "tokenizer_class": "EsmTokenizer",
43
+ "unk_token": "<unk>"
44
+ }
vocab.txt ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <unk>
2
+ <pad>
3
+ <mask>
4
+ <cls>
5
+ AAA
6
+ AAT
7
+ AAC
8
+ AAG
9
+ ATA
10
+ ATT
11
+ ATC
12
+ ATG
13
+ ACA
14
+ ACT
15
+ ACC
16
+ ACG
17
+ AGA
18
+ AGT
19
+ AGC
20
+ AGG
21
+ TAA
22
+ TAT
23
+ TAC
24
+ TAG
25
+ TTA
26
+ TTT
27
+ TTC
28
+ TTG
29
+ TCA
30
+ TCT
31
+ TCC
32
+ TCG
33
+ TGA
34
+ TGT
35
+ TGC
36
+ TGG
37
+ CAA
38
+ CAT
39
+ CAC
40
+ CAG
41
+ CTA
42
+ CTT
43
+ CTC
44
+ CTG
45
+ CCA
46
+ CCT
47
+ CCC
48
+ CCG
49
+ CGA
50
+ CGT
51
+ CGC
52
+ CGG
53
+ GAA
54
+ GAT
55
+ GAC
56
+ GAG
57
+ GTA
58
+ GTT
59
+ GTC
60
+ GTG
61
+ GCA
62
+ GCT
63
+ GCC
64
+ GCG
65
+ GGA
66
+ GGT
67
+ GGC
68
+ GGG
69
+ A
70
+ T
71
+ C
72
+ G
73
+ N
74
+ <eos>
75
+ <bos>