49 lines
1.1 KiB
Markdown
49 lines
1.1 KiB
Markdown
---
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language:
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- en
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license: apache-2.0
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tags:
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- gpt2
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- causal-lm
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- text-generation
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- tiny
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- testing
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pipeline_tag: text-generation
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---
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# gpt2-2layer-1m
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A **randomly-initialized**, 2-layer GPT-2 model for functional / integration testing.
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It produces incoherent text — that is by design.
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## Architecture
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| Hyperparameter | Value |
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|---|---|
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| Architecture | GPT-2 (decoder-only) |
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| Layers | 2 |
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| Hidden size | 256 |
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| Attention heads | 4 |
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| FFN inner size | 1 024 |
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| Context length | 512 |
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| Vocabulary size | 183 (byte-level BPE) |
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| Total params | ~1.76 M |
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| Non-embedding params | ~1.58 M |
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## Usage
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```python
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from transformers import GPT2LMHeadModel, PreTrainedTokenizerFast
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tokenizer = PreTrainedTokenizerFast.from_pretrained("gvadhul/gpt2-2layer-1m")
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model = GPT2LMHeadModel.from_pretrained("gvadhul/gpt2-2layer-1m")
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inputs = tokenizer("Hello world", return_tensors="pt")
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out = model.generate(**inputs, max_new_tokens=20)
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print(tokenizer.decode(out[0]))
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```
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## Intended use
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Functional / unit testing of pipelines that need a *tiny* causal LM.
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**Not suitable for any real NLP task** — weights are random.
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