初始化项目，由ModelHub XC社区提供模型

Model: solidrust/dolphin-2.9-llama3-8b-AWQ
Source: Original Platform

README.md

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+---
+license: other
+base_model: meta-llama/Meta-Llama-3-8B
+library_name: transformers
+tags:
+- 4-bit
+- AWQ
+- text-generation
+- autotrain_compatible
+- endpoints_compatible
+- generated_from_trainer
+pipeline_tag: text-generation
+inference: false
+quantized_by: Suparious
+datasets:
+- cognitivecomputations/Dolphin-2.9
+- teknium/OpenHermes-2.5
+- m-a-p/CodeFeedback-Filtered-Instruction
+- cognitivecomputations/dolphin-coder
+- cognitivecomputations/samantha-data
+- HuggingFaceH4/ultrachat_200k
+- microsoft/orca-math-word-problems-200k
+- abacusai/SystemChat-1.1
+- Locutusque/function-calling-chatml
+- internlm/Agent-FLAN
+---
+# cognitivecomputations/dolphin-2.9-llama3-8b AWQ
+
+Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
+
+Discord: https://discord.gg/8fbBeC7ZGx
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
+
+My appreciation for the sponsors of Dolphin 2.9:
+- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 10xL40S node
+
+This model is based on Llama-3-8b, and is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE)
+
+The base model has 8k context, and the full-weight fine-tuning was with 4k sequence length.
+
+It took 2.5 days on 8x L40S provided by Crusoe Cloud
+
+This model was trained FFT on all parameters, using ChatML prompt template format.
+
+example:
+
+```
+<|im_start|>system
+You are Dolphin, a helpful AI assistant.<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+
+```