Quantization made by Richard Erkhov.
microcoderfim-1B - AWQ
Original model description:
library_name: transformers
license: mit
language:
- en
metrics:
- bleu
- code_eval
- rouge
- chrf
model_name: MicroCoderFIM-1B
base_model: bigcode/starcoderbase-1b
model-index:
- name: MicroCoderFIM-1B
results:
- task:
type: text-generation
dataset:
type: openai_humaneval
name: HumanEval
metrics:
- name: pass@1
type: pass@1
value: 65.46
verified: false
- name: pass@10
type: pass@10
value: 90.36
verified: false
- name: pass@100
type: pass@100
value: 94.43
verified: false
- task:
type: text-generation
dataset:
type: xvadov01/cpp_emb_nl2pl
name: xvadov01/cpp_emb_nl2pl
metrics:
- name: BLEU
type: bleu
value: 31.74
verified: false
- name: codeBLEU
type: codeBLEU
value: 40.53
verified: false
- name: chrf++
type: chrf
value: 51.54
verified: false
- name: rouge-l
type: rouge
value: 43.31
verified: false
Model Card for Model ID
This is a finetuned version of StarCoderBase 1B using the
Fill-in-the-Middle objective on
dataset focused on embedded systems programming.
Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by: [More Information Needed]
- Shared by [optional]: [More Information Needed]
- Model type: Transformer decoder architecture with Multi-Query attention
- Language(s) (NLP): English
- License: MIT
- Finetuned from model [optional]: StarCoderBase 1B
Model Sources [optional]
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
Uses
Direct Use
[More Information Needed]
Downstream Use [optional]
[More Information Needed]
Out-of-Scope Use
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
Recommendations
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
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Summary
Model Examination [optional]
[More Information Needed]
Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
- Hardware Type: NVIDIA GeForce RTX 3090
- Hours used: 5h 25m
- Carbon Emitted: 0.83
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]
BibTeX:
[More Information Needed]
APA:
[More Information Needed]
Glossary [optional]
[More Information Needed]
More Information [optional]
[More Information Needed]
Model Card Authors [optional]
[More Information Needed]
Model Card Contact
[More Information Needed]
