Comments (3)
Does it refer to the accuracy of the EAGLE draft head in autoregressively predicting the next n tokens without using tree attention?
Yes. The input of the draft model is a feature sequence, part of which comes from the base model without errors, and part of which comes from the predictions of the draft model with errors. The acceptance rate of inputting n erroneous features is n-alpha.
from eagle.
Does it refer to the accuracy of the EAGLE draft head in autoregressively predicting the next n tokens without using tree attention?
Yes. The input of the draft model is a feature sequence, part of which comes from the base model without errors, and part of which comes from the predictions of the draft model with errors. The acceptance rate of inputting n erroneous features is n-alpha.
Thank you very much for your response; it has been extremely helpful to me.
I have a follow-up question regarding the term alpha_num. Could you please explain its meaning? Additionally, why is it necessary to divide alpha by alpha_num when calculating the accuracy of the draft head, rather than dividing alpha by the number of drafts?
I look forward to your clarification. Thank you once again for your assistance.
from eagle.
from eagle.
Related Issues (20)
- Any plan to support Llama 405B (Llama 3.1) HOT 3
- python -m eagle.ge_data.allocation --outdir [path of data] HOT 2
- How to use multi-GPU when gen data? HOT 2
- Any hint to improve average accept length for fine tuned LLAMA 70b? HOT 4
- ge_data_all_llama2chat
- Question about EAGLE-2 HOT 5
- Can Eagle2 use multi-gpus to inference? HOT 1
- Can Ealge2 use multi-gpus to inference? I mean data parallelism HOT 1
- Is this expected behavior? HOT 2
- Support Qwen2 in Eagle's inference framwork HOT 3
- Confusion in Figure 5 (b) of EAGLE2 paper HOT 2
- Will smaller models be supported? HOT 1
- Qwen2 inference HOT 8
- Actual parameter setting for different sizes of the model? HOT 1
- Reproduction Bias HOT 4
- Some questions that arise when studying your code HOT 2
- Can not reproduce speedup results reported in the paper. HOT 2
- When Train the Auto-regression Head, RuntimeError: CUDA error: device-side assert triggered
- what's the difference between ea_generate and eagenerate
- Evaluating Eagle on HumanEval, GSM8K, Alpaca, CNN/DM, and Natural Questions Datasets
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from eagle.