feat: adds phi model #1442
feat: adds phi model #1442
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|
You need to implement the flash one, the non flash are not interesting anymore and just kept as legacy. |
| # NOTE: this is the main difference between Llama and Phi | ||
| # in llama the rotary embeddings are applied to the whole query and key. | ||
| # Phi uses PARTIAL rotary embeddings, which are applied to the first 32 dimensions | ||
| # | ||
| # Apply partial positional embeddings in place | ||
| self.rotary_emb( | ||
| query[:, :, :self.num_heads], kv[:, 0, :, :self.num_heads], | ||
| cos, sin | ||
| ) |
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highlighting the most important lines here. Note only a portion of the query and key are rotary embedded.
|
Hey @OlivierDehaene would you mind taking a look at this model (specifically flash phi)? The non flash is only for legacy purposes. Notes: Outside of those changes there are a couple differences in weight naming and Phi uses bias. I think it makes sense to have Phi in a separate file rather than bloat the llama implementation. Please let me know if I should make any changes! Thanks 🙏 |
| use_medusa=use_medusa, | ||
| ) | ||
| else: | ||
| raise NotImplementedError(FLASH_ATT_ERROR_MESSAGE.format("Phi")) |
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Could we also load it with the Phi class based on CausalLM? Or is the layout different?
I'm not too familiar with Phi.
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thanks for the feedback!
yes, Phi can be loaded as a CausalLM with the 4.37.1 version of transformers. In my last PR I bumped the version, removed the NotImplementedError and tested that Phi works on my local cpu
server/text_generation_server/models/custom_modeling/flash_phi_modeling.py
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This PR adds basic modeling for phi-2
run
```bash
text-generation-server \
serve \
microsoft/phi-2 \
--revision 834565c23f9b28b96ccbeabe614dd906b6db551a
```
test
```bash
curl -s localhost:3000/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
-H 'Content-Type: application/json' | jq .
# {
# "generated_text": "\nDeep learning is a subset of machine learning that uses artificial neural networks to learn from data. These"
# }
```
notes
- recently (~1 day ago) the Phi weights and model were updated to
accommodate adding [GQA/MQA attention to the
model.](huggingface/transformers#28163) This
impl expects the original model format so a fixed revision is required
at the moment.
- this PR only includes a basic implementation of the model and can
later be extended for support Flash and Sharded versions as well as make
use of better optimization
This PR adds basic modeling for phi-2
run
```bash
text-generation-server \
serve \
microsoft/phi-2 \
--revision 834565c23f9b28b96ccbeabe614dd906b6db551a
```
test
```bash
curl -s localhost:3000/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
-H 'Content-Type: application/json' | jq .
```
notes
- recently (~1 day ago) the Phi weights and model were updated to
accommodate adding [GQA/MQA attention to the
model.](huggingface/transformers#28163) This
impl expects the original model format so a fixed revision is required
at the moment.
- this PR only includes a basic implementation of the model and can
later be extended for support Flash and Sharded versions as well as make
use of better optimization
This PR adds basic modeling for phi-2
run
text-generation-server \ serve \ microsoft/phi-2 \ --revision 834565c23f9b28b96ccbeabe614dd906b6db551atest
notes