Owen Arliawan
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Update README.md
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README.md
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@@ -5,9 +5,18 @@ Based on Meta-Llama-3-8b-Instruct, and is governed by Meta Llama 3 License agree
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https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b/blob/main/LICENSE
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We don't know how good this model is exactly since we have not benched this yet, but
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We are happy for anyone to try it out and give some feedback.
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You can try this model on our API at https://www.awanllm.com/
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Trained on 2048 sequence length, while the base model is 8192 sequence length. From testing it still performs the same 8192 context just fine.
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GGUF: https://huggingface.co/AwanLLM/Meta-Llama-3-8B-Dolphin-Lite-v0.1-GGUF
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4bpw: https://huggingface.co/AwanLLM/Meta-Llama-3-8B-Dolphin-Lite-v0.1-exl2-h8-4bpw-exl2
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https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b/blob/main/LICENSE
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We don't know how good this model is exactly in benchmarks since we have not benched this yet, but we think real prompts and usage is more telling anyways.
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From our testing this model is:
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- Less Refusals
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- More Uncensored
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- Follows requests better
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- Can reply in requested formats better without adding unnecesary information
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We are happy for anyone to try it out and give some feedback.
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You can also try this model on our API at https://www.awanllm.com/
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Trained on 2048 sequence length, while the base model is 8192 sequence length. From testing it still performs the same 8192 context just fine.
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GGUF: https://huggingface.co/AwanLLM/Meta-Llama-3-8B-Dolphin-Lite-v0.1-GGUF
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FP16: https://huggingface.co/AwanLLM/Meta-Llama-3-8B-Instruct-Dolphin-Lite
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Exllamav2:
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4bpw: https://huggingface.co/AwanLLM/Meta-Llama-3-8B-Dolphin-Lite-v0.1-exl2-h8-4bpw-exl2
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