---
library_name: transformers
language:
- sv
- en
---

# Lynx 2B (micro)
![Mascot](assets/lynx_mascot.png) 


## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Funded, Developed and shared by:** [42 Labs](https://www.42labs.ai)
- **Model type:** Auto-regressive transformer
- **Language(s) (NLP):** Swedish and English
- **License:** Gemma terms of use
- **Finetuned from model:** [Gemma 2B, 1.1 instruct](https://huggingface.co/google/gemma-1.1-2b-it)


## Uses

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### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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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

```python
import torch
from transformers import pipeline
from transformers import TextStreamer
from transformers import AutoTokenizer
from transformers import AutoModelForCausalLM


model_name = 'four-two-labs/lynx-micro'

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    device_map='cuda',
    torch_dtype=torch.bfloat16,
    use_flash_attention_2=True,  # Remove if flash attention isn't available
)

pipe = pipeline(
    'text-generation',    
    model=model,
    tokenizer=tokenizer,
    streamer=TextStreamer(tokenizer=tokenizer)
)

messages = [
    #{'role': 'user', 'content': 'Lös ekvationen 2x^2-5 = 9'},
    #{'role': 'user', 'content': 'Vad är fel med denna mening: "Hej! Jag idag bra mår."'},
    #{'role': 'user', 'content': """Översätt till svenska: Hayashi, the Japanese government spokesperson, said Monday that Tokyo is answering the Chinese presence around the islands with vessels of its own.\n\n“We ensure a comprehensive security system for territorial waters by deploying Coast Guard patrol vessels that are consistently superior to other party’s capacity,” Hayashi said.\n\nAny Japanese-Chinese incident in the Senkakus raises the risk of a wider conflict, analysts note, due to Japan’s mutual defense treaty with the United States.\n\nWashington has made clear on numerous occasions that it considers the Senkakus to be covered by the mutual defense pact."""},
    #{'role': 'user', 'content': """Vad handlar texten om?\n\nHayashi, the Japanese government spokesperson, said Monday that Tokyo is answering the Chinese presence around the islands with vessels of its own.\n\n“We ensure a comprehensive security system for territorial waters by deploying Coast Guard patrol vessels that are consistently superior to other party’s capacity,” Hayashi said.\n\nAny Japanese-Chinese incident in the Senkakus raises the risk of a wider conflict, analysts note, due to Japan’s mutual defense treaty with the United States.\n\nWashington has made clear on numerous occasions that it considers the Senkakus to be covered by the mutual defense pact."""},
    #{'role': 'user', 'content': """Skriv en sci-fi novell som utspelar sig över millenium på en planet runt ett binärt stjärnsystem."""},
    {'role': 'user', 'content': 'Hur många helikoptrar kan en människa äta på en gång?'},
]

r = pipe(
    messages,
    max_length=4096, 
    do_sample=False,     
    eos_token_id=tokenizer.vocab['<end_of_turn>']
)
```



## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### 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]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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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]
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- **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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**BibTeX:**

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**APA:**

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## Glossary [optional]

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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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