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OpenSeek-Small v1 Model Documentation
Overview
OpenSeek-Small-v1 is the initial production model of the OpenSeek project.
- Utilizes DeepSeek-V3-like MoE architecture.
- Comprises 1.4 billion total parameters, with 0.4 billion activated parameters.
- Trained on 720 billion tokens.
- Completely broken in stock form.
Key Fixes in this repository:
- Fixed Broken Position Embeddings
- Fixed Fundamental Incompatibilities Between Deepseekv3 Model and Qwen Tokenizer.
Usage Instructions
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Robertp423/OpenSeek-Fixed",trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("Robertp423/OpenSeek-Fixed",trust_remote_code=True)
inputs = tokenizer("The future of AI is", return_tensors="pt")
inputs.pop("token_type_ids", None) # Critical fix
outputs = model.generate(**inputs, max_length=50)
print(tokenizer.decode(outputs[0]))
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