CortexLM
/

btlm-7b-base-v0.2

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 ---
+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 v0.2**
+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 :** 06-06-2024
+[**Subnet 9 Network Leaderboard**](https://huggingface.co/spaces/RaoFoundation/pretraining-leaderboard)
+[**Top Bittensor Model Checkpoint**](https://huggingface.co/jw-hf-test/jw2)
+### Inference
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+import torch
+model = "CortexLM/btlm-7b-base-v0.2"
+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 |
+| --- | --- | --- | --- | --- | --- | --- |
+[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.