KeisukeMiyamoto commited on
Commit
6da4e76
·
verified ·
1 Parent(s): b9dc1d6

Add model card

Browse files
Files changed (1) hide show
  1. README.md +59 -0
README.md ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - ja
4
+ library_name: transformers
5
+ tags:
6
+ - lambda
7
+ - causal-lm
8
+ - custom-code
9
+ - pytorch
10
+ pipeline_tag: text-generation
11
+ ---
12
+
13
+ # lambda-1-360m-mid
14
+
15
+ lambda-1-360m-mid is an experimental Japanese language model based on [`lambda-1-360m-base`](https://huggingface.co/KeisukeMiyamoto/lambda-1-360m-base) and further pretrained on a synthetic Japanese textbook corpus.
16
+
17
+ All training code is publicly available at [KeisukeMiyamoto1324/lambda](https://github.com/KeisukeMiyamoto1324/lambda).
18
+
19
+ ## Model Details
20
+
21
+ | Item | Value |
22
+ |---|---:|
23
+ | Parameters | 359.9M |
24
+ | Architecture | Decoder-only Transformer |
25
+ | Context length | 1,024 tokens |
26
+ | Tokenizer | Byte-level BPE |
27
+ | Vocabulary size | 65,536 |
28
+ | Layers | 32 |
29
+ | Hidden size | 960 |
30
+ | Attention heads | 15 |
31
+ | Key-value heads | 5 |
32
+ | FFN size | 4,096 |
33
+
34
+ ## Training Data
35
+
36
+ The base model was pretrained on [`KeisukeMiyamoto/lambda-corpus`](https://huggingface.co/datasets/KeisukeMiyamoto/lambda-corpus).
37
+
38
+ This model was then further pretrained on [`KeisukeMiyamoto/SyntheticTextbook-jp`](https://huggingface.co/datasets/KeisukeMiyamoto/SyntheticTextbook-jp) for 20,480 steps.
39
+
40
+ ## Usage
41
+
42
+ ```bash
43
+ git clone https://github.com/KeisukeMiyamoto1324/lambda.git
44
+ cd lambda
45
+ python3 -m venv venv
46
+ source venv/bin/activate
47
+ pip3 install -r requirements.txt
48
+
49
+ python3 src/inference_base/inference_hf.py \
50
+ --model-dir "KeisukeMiyamoto/lambda-1-360m-mid" \
51
+ --prompt "人工知能とは" \
52
+ --max-new-tokens 64
53
+ ```
54
+
55
+ ## Limitations
56
+
57
+ This model is not instruction-tuned or safety-aligned. It may generate incorrect, biased, unsafe, or low-quality text.
58
+
59
+ The model was trained primarily on Japanese text and has not been evaluated on standard benchmarks.