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dolphin-2.9-llama3-8b-AWQ

Text Generation
Transformers
Safetensors
llama
4-bit precision
AWQ
Inference Endpoints
Generated from Trainer
conversational
text-generation-inference
awq
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dolphin-2.9-llama3-8b-AWQ / README.md
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metadata
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

My appreciation for the sponsors of Dolphin 2.9:

This model is based on Llama-3-8b, and is governed by META LLAMA 3 COMMUNITY LICENSE AGREEMENT

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