Skip to content

Update Llama README.md for Stories110M tokenizer #5975

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Oct 8, 2024
Merged

Update Llama README.md for Stories110M tokenizer #5975

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
15 changes: 7 additions & 8 deletions examples/models/llama2/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -113,11 +113,6 @@ If you want to deploy and run a smaller model for educational purposes. From `ex
```
python -m examples.models.llama2.export_llama -c stories110M.pt -p params.json -X -kv
```
4. Create tokenizer.bin.

```
python -m extension.llm.tokenizer.tokenizer -t <tokenizer.model> -o tokenizer.bin
```

### Option C: Download and export Llama 3 8B instruct model

Expand All @@ -127,7 +122,11 @@ You can export and run the original Llama 3 8B instruct model.

2. Export model and generate `.pte` file
```
python -m examples.models.llama2.export_llama --checkpoint <consolidated.00.pth> -p <params.json> -kv --use_sdpa_with_kv_cache -X -qmode 8da4w --group_size 128 -d fp32 --metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001]}' --embedding-quantize 4,32 --output_name="llama3_kv_sdpa_xnn_qe_4_32.pte"
python -m examples.models.llama2.export_llama --checkpoint <checkpoint.pth> --params <params.json> -kv --use_sdpa_with_kv_cache -X -qmode 8da4w --group_size 128 -d fp32
```
4. Create tokenizer.bin.
```
python -m extension.llm.tokenizer.tokenizer -t <tokenizer.model> -o tokenizer.bin
```

Due to the larger vocabulary size of Llama 3, we recommend quantizing the embeddings with `--embedding-quantize 4,32` as shown above to further reduce the model size.
Expand Down Expand Up @@ -187,7 +186,7 @@ tokenizer.path=<path_to_checkpoint_folder>/tokenizer.model

Using the same arguments from above
```
python -m examples.models.llama2.eval_llama -c <checkpoint.pth> -p <params.json> -t <tokenizer.model> -d fp32 --max_seq_len <max sequence length> --limit <number of samples>
python -m examples.models.llama2.eval_llama -c <checkpoint.pth> -p <params.json> -t <tokenizer.model/bin> -d fp32 --max_seq_len <max sequence length> --limit <number of samples>
```

The Wikitext results generated above used: `{max_seq_len: 2048, limit: 1000}`
Expand Down Expand Up @@ -233,7 +232,7 @@ Note for Mac users: There's a known linking issue with Xcode 15.1. Refer to the
cmake-out/examples/models/llama2/llama_main --model_path=<model pte file> --tokenizer_path=<tokenizer.bin> --prompt=<prompt>
```

For Llama3, you can pass the original `tokenizer.model` (without converting to `.bin` file).
For Llama2 models, pass the converted `tokenizer.bin` file instead of `tokenizer.model`.

To build for CoreML backend and validate on Mac, replace `-DEXECUTORCH_BUILD_XNNPACK=ON` with `-DEXECUTORCH_BUILD_COREML=ON`

Expand Down
Loading