|
--- |
|
library_name: nanoGPT |
|
tags: [] |
|
--- |
|
|
|
# Model Card for Model ID |
|
|
|
<!-- Provide a quick summary of what the model is/does. --> |
|
|
|
|
|
|
|
## Model Details |
|
|
|
### Model Description |
|
|
|
<!-- Provide a longer summary of what this model is. --> |
|
|
|
This is the model card of a model trained by Karpathy's [nanoGPT](https://github.com/karpathy/nanoGPT). The vocabulary size is 20_000 and the context window is 1024.<br> |
|
The model is trined on tripathysagar/odia-news, news paper article extracted from odia daily [Dharitri](https://www.dharitri.com). |
|
|
|
## Uses |
|
|
|
```python |
|
>>> from huggingface_hub import snapshot_download |
|
>>> snapshot_download(repo_id="tripathysagar/odia-gpt", local_dir='.') |
|
|
|
>>> from model import GPT |
|
>>> import os, torch |
|
|
|
>>> from tokenizers import Tokenizer |
|
>>> tokenizer = Tokenizer.from_file('tokenizer.json') |
|
>>> nn, _ = GPT.from_file(os.path.join('model.pt')) |
|
>>> nn = nn.to('cuda') |
|
|
|
>>> s = 'କ୍ରେଡିଟ କାର୍ଡ ନେବା ସମୟରେ ଏହାର ସର୍ତ୍ତ ଏବଂ ନିୟମଗୁଡ଼ିକୁ ଧ୍ୟାନର ସହିତ ପଢ଼ିବା ଉଚିତ ।' |
|
>>> enc = torch.tensor(tokenizer.encode(s).ids).unsqueeze(0).to('cuda') |
|
|
|
>>> op = nn.generate(enc, 50, top_k=50) |
|
|
|
>>> print(tokenizer.decode(op[0].to('cpu').tolist())) |
|
``` |
|
### Direct Use |
|
|
|
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
|
|
|
|
|
## Training Details |
|
|
|
### Training Data |
|
|
|
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
|
|
|
[More Information Needed] |
|
|
|
### Training Procedure |
|
|
|
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
|
|
|
#### Preprocessing [optional] |
|
|
|
[More Information Needed] |
|
|
|
|
|
#### Training Hyperparameters |
|
|
|
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
|
|
|
#### Speeds, Sizes, Times [optional] |
|
|
|
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
|
|
|
[More Information Needed] |
|
|
|
## Evaluation |
|
|
|
<!-- This section describes the evaluation protocols and provides the results. --> |
|
|
|
### Testing Data, Factors & Metrics |
|
|
|
#### Testing Data |
|
|
|
<!-- This should link to a Dataset Card if possible. --> |
|
|
|
[More Information Needed] |
|
|
|
#### Factors |
|
|
|
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
|
|
|
[More Information Needed] |
|
|
|
#### Metrics |
|
|
|
<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
|
|
|
[More Information Needed] |
|
|
|
### Results |
|
|
|
[More Information Needed] |
|
|
|
#### Summary |
|
|
|
|
|
|
