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README.md

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----
-base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
-library_name: peft
-pipeline_tag: text-generation
-tags:
-- base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0
-- lora
-- transformers
----
-
-# 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. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
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-### Downstream Use [optional]
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-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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-### Out-of-Scope Use
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-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-## Bias, Risks, and Limitations
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-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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-[More Information Needed]
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-### Recommendations
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-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## 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. -->
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-[More Information Needed]
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-### Training Procedure
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-<!-- 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]
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-
-#### Training Hyperparameters
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-- **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. -->
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-[More Information Needed]
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-## Evaluation
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-<!-- This section describes the evaluation protocols and provides the results. -->
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-### Testing Data, Factors & Metrics
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-#### Testing Data
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-<!-- This should link to a Dataset Card if possible. -->
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-#### Factors
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-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-#### Metrics
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-### Results
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-#### Summary
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-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
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-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
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-### Compute Infrastructure
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-#### Hardware
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-#### Software
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-## Citation [optional]
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-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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-**BibTeX:**
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-**APA:**
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-## Glossary [optional]
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-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-## More Information [optional]
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-## Model Card Authors [optional]
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-## Model Card Contact
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-### Framework versions
-
-- PEFT 0.18.0
+# Test LoRA Adapter for SGLang Embedding LoRA
+
+This is a test LoRA adapter (randomly initialized without tuning) for testing SGLang's embedding LoRA implementation.
+
+## Configuration
+
+- **Base model:** `TinyLlama/TinyLlama-1.1B-Chat-v1.0`
+- **LoRA rank (r):** 8
+- **LoRA alpha:** 16
+- **Target modules:** embed_tokens, lm_head, q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+
+## Weight Shapes
+
+```
+down_proj.lora_A: (8, 5632)
+down_proj.lora_B: (2048, 8)
+embed_tokens.lora_embedding_A: (8, 32000)
+embed_tokens.lora_embedding_B: (2048, 8)
+gate_proj.lora_A: (8, 2048)
+gate_proj.lora_B: (5632, 8)
+k_proj.lora_A: (8, 2048)
+k_proj.lora_B: (256, 8)
+lm_head.lora_A: (8, 2048)
+lm_head.lora_B: (32000, 8)
+o_proj.lora_A: (8, 2048)
+o_proj.lora_B: (2048, 8)
+q_proj.lora_A: (8, 2048)
+q_proj.lora_B: (2048, 8)
+up_proj.lora_A: (8, 2048)
+up_proj.lora_B: (5632, 8)
+v_proj.lora_A: (8, 2048)
+v_proj.lora_B: (256, 8)
+```
+
+## Purpose
+
+This adapter tests that SGLang's `ChunkedSgmvLoRABackend.run_lora_a_embedding()` correctly handles embedding LoRA layers (`embed_tokens`, `lm_head`).
+
+**Key:** `embed_tokens` is in `target_modules` (LoRA decomposition), NOT `modules_to_save` (full weights).
+
+## Usage with SGLang
+
+```python
+# This adapter contains randomly initialized weights for testing purposes only.
+# Used by: test/srt/lora/test_lora_hf_sgl_logprob_diff.py
+```
+
+## Created with
+
+```bash
+python scripts/playground/lora/create_embedding_lora_adapter.py
+```

adapter_config.json

@@ -30,9 +30,14 @@
   "revision": null,
   "target_modules": [
     "q_proj",
+    "up_proj",
     "v_proj",
+    "gate_proj",
+    "embed_tokens",
     "lm_head",
-    "embed_tokens"
+    "o_proj",
+    "down_proj",
+    "k_proj"
   ],
   "target_parameters": null,
   "task_type": "CAUSAL_LM",

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:875d7c0b9c037fb989d19ec3173cdab3fb2edf6cc73c9030ab5aa7bd1ae1273d
-size 268840968
+oid sha256:656a39751852f5b1143f92ffd5d5a501cb1a70dcd0f6509fb1e6e40eb9aeefdf
+size 289595592

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
+size 499723