初始化项目，由ModelHub XC社区提供模型

Model: QuantFactory/Samantha-Qwen-2-7B-GGUF
Source: Original Platform

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README.md

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+---
+base_model: macadeliccc/Samantha-Qwen-2-7B
+datasets:
+- macadeliccc/opus_samantha
+- HuggingfaceH4/ultrachat_200k
+- teknium/OpenHermes-2.5
+- Sao10K/Claude-3-Opus-Instruct-15K
+license: apache-2.0
+language:
+- en
+- zh
+pipeline_tag: text-generation
+---
+# Samantha Qwen2 7B-GGUF
+This is quantized version of [macadeliccc/Samantha-Qwen-2-7B](https://huggingface.co/macadeliccc/Samantha-Qwen-2-7B) created using llama.cpp
+
+# Model Description
+
+Trained on 2x4090 using QLoRa and FSDP
+
++ [LoRa](macadeliccc/Samantha-Qwen2-7B-LoRa)
+
+## Launch Using VLLM
+
+```bash
+python -m vllm.entrypoints.openai.api_server \
+    --model macadeliccc/Samantha-Qwen-2-7B \
+    --chat-template ./examples/template_chatml.jinja \
+```
+
+```python
+from openai import OpenAI
+# Set OpenAI's API key and API base to use vLLM's API server.
+openai_api_key = "EMPTY"
+openai_api_base = "http://localhost:8000/v1"
+
+client = OpenAI(
+    api_key=openai_api_key,
+    base_url=openai_api_base,
+)
+
+chat_response = client.chat.completions.create(
+    model="macadeliccc/Samantha-Qwen-2-7B",
+    messages=[
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Tell me a joke."},
+    ]
+)
+print("Chat response:", chat_response)
+```
+
+## Prompt Template
+
+```
+<|im_start|>system
+You are  a friendly assistant.<|im_end|>
+<|im_start|>user
+What is the capital of France?<|im_end|>
+<|im_start|>assistant
+The capital of France is Paris.
+```
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.0`
+```yaml
+base_model: Qwen/Qwen-7B
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+datasets:
+  - path: macadeliccc/opus_samantha
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: uncensored-ultrachat.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: openhermes_200k.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: opus_instruct.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+
+chat_template: chatml
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./outputs/lora-out
+
+sequence_len: 2048
+sample_packing: false
+pad_to_sequence_len:
+
+adapter: qlora
+lora_model_dir:
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 1
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: false
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention:
+
+warmup_steps: 250
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+```
+
+</details><br>

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configuration.json

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