初始化项目，由ModelHub XC社区提供模型
Model: kyutai/helium-1-preview-2b Source: Original Platform
This commit is contained in:
ModelHub XC
202
README.md
Normal file
202
README.md
Normal file
@@ -0,0 +1,202 @@
|
||||
---
|
||||
library_name: transformers
|
||||
license: cc-by-4.0
|
||||
language:
|
||||
- en
|
||||
- fr
|
||||
- de
|
||||
- it
|
||||
- pt
|
||||
- es
|
||||
pipeline_tag: text-generation
|
||||
---
|
||||
|
||||
# helium-1-preview-2b
|
||||
|
||||
<!-- Provide a quick summary of what the model is/does. -->
|
||||
|
||||
<img src="https://huggingface.co/kyutai/moshi-1-2b/resolve/main/helium_sticker.png" width="400">
|
||||
|
||||
## Model Details
|
||||
|
||||
### Model Description
|
||||
|
||||
<!-- Provide a longer summary of what this model is. -->
|
||||
|
||||
Helium-1 preview is a lightweight language model with 2B parameters, targeting edge and mobile devices.
|
||||
It supports the following languages: English, French, German, Italian, Portuguese, Spanish.
|
||||
|
||||
⚠️ Helium-1 Preview is a base model, which was not fine-tuned to follow instructions or human preferences.
|
||||
For most downstream use cases, the model should be aligned with supervised fine-tuning, RLHF or related methods.
|
||||
|
||||
- **Developed by:** Kyutai
|
||||
- **Model type:** Large Language Model
|
||||
- **Language(s) (NLP):** English, French, German, Italian, Portuguese, Spanish
|
||||
- **License:** CC-BY 4.0
|
||||
|
||||
<!-- ### 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. -->
|
||||
|
||||
The intended use of the Helium model is research and development of natural language processing systems, including but not limited to language generation and understanding.
|
||||
The model can be used in English, French, German, Italian, Portuguese and Spanish.
|
||||
For most downstream use cases, the model should be aligned with supervised fine-tuning, RLHF or related methods.
|
||||
|
||||
### Out-of-Scope Use
|
||||
|
||||
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
||||
|
||||
The model should not be used in other languages than the ones on which it was trained.
|
||||
The model is not intended to be used for any malicious or illegal activities of any kind.
|
||||
The model was not fine-tuned to follow instructions, and thus should not be used as such.
|
||||
|
||||
## Bias, Risks, and Limitations
|
||||
|
||||
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
||||
|
||||
Helium-1 preview is a base language model, which was not aligned to human preferences.
|
||||
As such, the model can generate incorrect, biased, harmful or generally unhelpful content.
|
||||
Thus, the model should not be used for downstream applications without further alignment, evaluations and mitigations of risks.
|
||||
<!-- Thus, it should not be used without further evaluations of risks and mitigations. -->
|
||||
|
||||
## How to Get Started with the Model
|
||||
|
||||
Use the code below to get started with the model.
|
||||
|
||||
```python
|
||||
import torch
|
||||
from transformers import pipeline
|
||||
|
||||
model_id = "kyutai/helium-1-preview-2b"
|
||||
|
||||
pipe = pipeline(
|
||||
"text-generation",
|
||||
model=model_id,
|
||||
torch_dtype=torch.bfloat16,
|
||||
device_map="auto"
|
||||
)
|
||||
|
||||
text = pipe("Hello, today is a great day to")
|
||||
```
|
||||
|
||||
## 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. -->
|
||||
|
||||
Helium-1 preview was trained on a mix of data including: Wikipedia, Stack Exchange, open-access scientific articles (from peS2o) and Common Crawl.
|
||||
|
||||
<!--#### 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 -->
|
||||
|
||||
## Evaluation
|
||||
|
||||
<!-- This section describes the evaluation protocols and provides the results. -->
|
||||
|
||||
#### Testing Data
|
||||
|
||||
<!-- This should link to a Dataset Card if possible. -->
|
||||
|
||||
The model was evaluated on MMLU, TriviaQA, NaturalQuestions, ARC Easy & Challenge, Open Book QA, Common Sense QA,
|
||||
Physical Interaction QA, Social Interaction QA, HellaSwag, WinoGrande, Multilingual Knowledge QA, FLORES 200.
|
||||
|
||||
#### Metrics
|
||||
|
||||
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
||||
|
||||
We report accuracy on MMLU, ARC, OBQA, CSQA, PIQA, SIQA, HellaSwag, WinoGrande.
|
||||
We report exact match on TriviaQA, NQ and MKQA.
|
||||
We report BLEU on FLORES.
|
||||
|
||||
#### English Results
|
||||
|
||||
| Benchmark | Helium-1 Preview | HF SmolLM2 (1.7B) | Gemma-2 (2.6B) | Llama-3.2 (3B) | Qwen2.5 (1.5B) |
|
||||
|--------------|:------:|:------:|:------:|:------:|:------:|
|
||||
| | | | | | |
|
||||
| MMLU | 51.2 | 50.4 | 53.1 | 56.6 | 61.0 |
|
||||
| NQ | 17.3 | 15.1 | 17.7 | 22.0 | 13.1 |
|
||||
| TQA | 47.9 | 45.4 | 49.9 | 53.6 | 35.9 |
|
||||
| ARC E | 80.9 | 81.8 | 81.1 | 84.6 | 89.7 |
|
||||
| ARC C | 62.7 | 64.7 | 66.0 | 69.0 | 77.2 |
|
||||
| OBQA | 63.8 | 61.4 | 64.6 | 68.4 | 73.8 |
|
||||
| CSQA | 65.6 | 59.0 | 64.4 | 65.4 | 72.4 |
|
||||
| PIQA | 77.4 | 77.7 | 79.8 | 78.9 | 76.0 |
|
||||
| SIQA | 64.4 | 57.5 | 61.9 | 63.8 | 68.7 |
|
||||
| HS | 69.7 | 73.2 | 74.7 | 76.9 | 67.5 |
|
||||
| WG | 66.5 | 65.6 | 71.2 | 72.0 | 64.8 |
|
||||
| | | | | | |
|
||||
| Average | 60.7 | 59.3 | 62.2 | 64.7 | 63.6 |
|
||||
|
||||
#### Multilingual Results
|
||||
|
||||
| Language | Benchmark | Helium-1 Preview | HF SmolLM2 (1.7B) | Gemma-2 (2.6B) | Llama-3.2 (3B) | Qwen2.5 (1.5B) |
|
||||
|-----|--------------|:------:|:------:|:------:|:------:|:------:|
|
||||
| | | | | | | |
|
||||
| German | MMLU | 45.6 | 35.3 | 45.0 | 47.5 | 49.5 |
|
||||
| | ARC C | 56.7 | 38.4 | 54.7 | 58.3 | 60.2 |
|
||||
| | HS | 53.5 | 33.9 | 53.4 | 53.7 | 42.8 |
|
||||
| | MKQA | 16.1 | 7.1 | 18.9 | 20.2 | 10.4 |
|
||||
| | FLORES | 33.9 | 12.2 | 30.7 | 28.2 | 20.8 |
|
||||
| Spanish | MMLU | 46.5 | 38.9 | 46.2 | 49.6 | 52.8 |
|
||||
| | ARC C | 58.3 | 43.2 | 58.8 | 60.0 | 68.1 |
|
||||
| | HS | 58.6 | 40.8 | 60.5 | 61.1 | 51.4 |
|
||||
| | MKQA | 16.0 | 7.9 | 18.5 | 20.6 | 10.6 |
|
||||
| | FLORES | 25.7 | 15.0 | 25.7 | 23.7 | 20.4 |
|
||||
| French | MMLU | 46.0 | 37.7 | 45.7 | 48.8 | 51.9 |
|
||||
| | ARC C | 57.9 | 40.6 | 57.5 | 60.1 | 67.4 |
|
||||
| | HS | 59.0 | 41.1 | 60.4 | 59.6 | 51.2 |
|
||||
| | MKQA | 16.8 | 8.4 | 18.4 | 19.6 | 9.7 |
|
||||
| | FLORES | 44.3 | 20.0 | 43.3 | 39.3 | 31.2 |
|
||||
| Italian | MMLU | 46.1 | 36.3 | 45.6 | 48.8 | 50.5 |
|
||||
| | ARC C | 57.4 | 39.1 | 53.9 | 60.1 | 64.6 |
|
||||
| | HS | 55.2 | 37.7 | 56.2 | 56.8 | 46.8 |
|
||||
| | MKQA | 15.3 | 6.3 | 18.0 | 19.0 | 9.9 |
|
||||
| | FLORES | 25.8 | 10.4 | 25.2 | 23.8 | 16.4 |
|
||||
| Portuguese | MMLU | 46.2 | 37.7 | 45.6 | 49.2 | 53.0 |
|
||||
| | ARC C | 56.8 | 40.6 | 57.0 | 62.1 | 66.6 |
|
||||
| | HS | 57.3 | 41.0 | 58.7 | 59.1 | 50.9 |
|
||||
| | MKQA | 14.7 | 6.6 | 16.9 | 19.1 | 9.2 |
|
||||
| | FLORES | 43.0 | 20.0 | 43.6 | 40.5 | 33.0 |
|
||||
| | | | | | | |
|
||||
| | Average | 42.1 | 27.8 | 42.3 | 43.6 | 40.0
|
||||
|
||||
## Technical Specifications
|
||||
|
||||
### Model Architecture and Objective
|
||||
|
||||
| Hyperparameter | Value |
|
||||
|--------------|:------:|
|
||||
| Layers | 24 |
|
||||
| Heads | 20 |
|
||||
| Model dimension | 2560 |
|
||||
| MLP dimension | 7040 |
|
||||
| Context size | 4096 |
|
||||
| Theta RoPE | 100,000 |
|
||||
|
||||
#### Hardware
|
||||
|
||||
The model was trained on 128 NVIDIA H100 Tensor Core GPUs.
|
||||
|
||||
#### Software
|
||||
|
||||
The model was trained using Jax.
|
||||
|
||||
## Citation
|
||||
|
||||
Blog post: https://kyutai.org/2025/01/13/helium.html
|
||||
Reference in New Issue
Block a user