README.md

---
license: mit
library_name: transformers
tags:
- bittensor
- decentralization
- subnet 9
datasets:
- tiiuae/falcon-refinedweb
---
<img src="https://cdn-uploads.huggingface.co/production/uploads/655a0bdf3ff5ba1b1b1c01b7/y1dKBZh8UhII6wtbs5boj.png" alt="drawing" width="512"/>

# 🚀 **BTLM-7B v0.1**
BTLM (Bittensor Language Model) is a collection of pretrained generative text models. This is the repository for the 7B pretrained model, optimized for dialogue use cases and converted for the HF中国镜像站 Transformers format.

### Model Details

Bittensor's decentralized subnet 9 facilitated the development and release of the first version of the BTLM-7B model. This initial release comprises a sophisticated large language model designed for a variety of applications.In creating this model, significant effort was made to ensure its effectiveness and safety, setting a new standard in the decentralized open-source AI community.

⛔ **This is a pretrained model, which should be further finetuned for most usecases.** 

**Training subnetwork :** 9

**Checkpoint :** 03-05-2024

[**Subnet 9 Network Leaderboard**](https://huggingface.co/spaces/macrocosm-os/pretraining-leaderboard)

[**Top Bittensor Model Checkpoint**](https://huggingface.co/tensorplex-labs/pretraining-sn9-7B-1)

### Inference

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch

model = "CortexLM/btlm-7b-base-v0.1"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    torch_dtype=torch.bfloat16,
)
sequences = pipeline(
   "Tell me about decentralization.",
    max_length=200,
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id,
)
for seq in sequences:
    print(f"Result: {seq['generated_text']}")

```

### Benchmark

| Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
| --- | --- | --- | --- | --- | --- | --- |
|  43.32  | 45.65 | 58.29  | 44.26 | 30.45 | 70.88 | 10.39 |

[LM Evaluation Harness Repository](https://github.com/EleutherAI/lm-evaluation-harness)

## License
BTLM-7B is licensed under the [MIT License](https://opensource.org/license/mit), a permissive license that allows for reuse with virtually no restrictions.