Llama-Q4V / README.md
jleuth's picture
Update README.md
f5b19b1 verified
|
raw
history blame
7.27 kB
---
license: mit
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: transformers
tags: ["meta", "llama", "voice", "question-answering"]
---
# Model Card for Llama-Q4V
<!-- Provide a quick summary of what the model is/does. -->
Llama-Q4V is a quantized and voice-optimized version of Llama-3.1-8B-Instruct, and is the core LLM for Ai Tag, an open source $20 competitor to Humane's Ai Pin.
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed, Funded, and Shared by:** Jacob Leuthardt
- **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]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- 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. -->
[More Information Needed]
### Training Procedure
<!-- 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]
#### Training Hyperparameters
- **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. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
Llama-Q4V was evaluated on HellaSwag, GLUE, and TriviaQA
| Tasks |Version| Filter |n-shot| Metric | |Value | |Stderr|
|----------------|-------|-----------------|-----:|-----------|---|-----:|---|-----:|
| - cola | 1|none | 0|mcc |↑ |0.0409|± |0.0323|
|glue |N/A |none | 0|acc |↑ |0.5002|± |0.0019|
| | |none | 0|f1 |↑ |0.5789|± |0.0026|
| | |none | 0|mcc |↑ |0.0409|± |0.0323|
|hellaswag | 1|none | 0|acc |↑ |0.5849|± |0.0049|
| | |none | 0|acc_norm |↑ |0.7846|± |0.0041|
| - mnli | 1|none | 0|acc |↑ |0.5200|± |0.0050|
| - mnli_mismatch| 1|none | 0|acc |↑ |0.5098|± |0.0050|
| - mrpc | 1|none | 0|acc |↑ |0.6887|± |0.0230|
| | |none | 0|f1 |↑ |0.8113|± |0.0165|
| - qnli | 1|none | 0|acc |↑ |0.5032|± |0.0068|
| - qqp | 2|none | 0|acc |↑ |0.4816|± |0.0025|
| | |none | 0|f1 |↑ |0.5765|± |0.0027|
| - rte | 1|none | 0|acc |↑ |0.6679|± |0.0283|
| - sst2 | 1|none | 0|acc |↑ |0.8612|± |0.0117|
|triviaqa | 3|remove_whitespace| 0|exact_match|↑ |0.4962|± |0.0037|
| - wnli | 2|none | 0|acc |↑ |0.6197|± |0.0580|
|Groups|Version|Filter|n-shot|Metric| |Value | |Stderr|
|------|-------|------|-----:|------|---|-----:|---|-----:|
|glue |N/A |none | 0|acc |↑ |0.5002|± |0.0019|
| | |none | 0|f1 |↑ |0.5789|± |0.0026|
| | |none | 0|mcc |↑ |0.0409|± |0.0323|
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[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
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]