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.gitattributes CHANGED
@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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+ ReSearch-Qwen-7B.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
LICENSE ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ MIT License
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+
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+ Copyright (c) 2025 Agent-RL
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+
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+ Permission is hereby granted, free of charge, to any person obtaining a copy
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+ of this software and associated documentation files (the "Software"), to deal
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+ in the Software without restriction, including without limitation the rights
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+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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+ copies of the Software, and to permit persons to whom the Software is
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+ furnished to do so, subject to the following conditions:
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+
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+ The above copyright notice and this permission notice shall be included in all
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+ copies or substantial portions of the Software.
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+
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+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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+ SOFTWARE.
ModelFile ADDED
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+ FROM ReSearch-Qwen-7B.Q8_0.gguf
README.md ADDED
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+ ---
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+ base_model: agentrl/ReSearch-Qwen-7B
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+ datasets:
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+ - RUC-NLPIR/FlashRAG_datasets
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+ language:
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+ - en
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+ library_name: transformers
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+ license: mit
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+ quantized_by: mradermacher
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+ pipeline_tag: text-generation
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+ tags:
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+ - function-calling
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+ - tool-calling
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+ - codex
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+ - local-llm
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+ - gguf
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+ - 6gb-vram
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+ - ollama
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+ - code-assistant
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+ - api-tools
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+ - openai-alternative
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+ ---
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+
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+ This is a packged Q8_0 only model from https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF that runs on 9-12GB VRAM without any quality loss.
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+
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+
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+
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+
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+ <!-- ### quantize_version: 2 -->
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+ <!-- ### output_tensor_quantised: 1 -->
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+ <!-- ### convert_type: hf -->
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+ <!-- ### vocab_type: -->
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+ <!-- ### tags: -->
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+
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+ <!-- provided-files -->
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+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/ReSearch-Qwen-7B-i1-GGUF
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+
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+
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+ </div>
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+
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+ <p align="center">
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+ <img src="https://huggingface.co/agentrl/ReSearch-Qwen-7B/blob/main/assets/intro_bar.png" width="90%" alt="Intro" />
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+ <img src="https://huggingface.co/agentrl/ReSearch-Qwen-7B/blob/main/assets/method.png" width="90%" alt="Method" />
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+ </p>
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+
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+
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+ For this base model DONT apply the chat completion
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+
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+ ## Setup
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+
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+ Install ollama
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+ ```bash
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+ curl -fsSL https://ollama.com/install.sh | sh
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+ ```
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+
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+ Go into your favourite folder
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+
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+ ```bash
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+ # make sure you hve Python 3.8+
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+ # apt-get update && apt-get install libcurl build-essential curl
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+ pip install huggingface-hub ollama
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+ huggingface-cli download Manojb/Qwen-7B-toolcalling-ReSearch-gguf-Q8_0 --download-dir Qwen-7B-toolcalling-ReSearch-gguf-Q8_0
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+ cd "$(find . -type d -iname '*Qwen-7B-toolcalling-ReSearch-gguf-Q8_0*' | head -n 1)"
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+ source run_model.sh
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+ ```
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+
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+ Or
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+
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+ ```bash
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+ # Download and run instantly
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+ ollama create qwen-7b:toolcall -f ModelFile
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+ ollama run qwen-7b:toolcall # without chat completion
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+ ```
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+
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+
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+ ### Basic Function Calling
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+ ```python
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+ # Load with Ollama
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+ import requests
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+
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+ response = requests.post('http://localhost:11434/api/generate', json={
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+ 'model': 'qwen-7b:toolcall',
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+ 'prompt': 'Get the current weather in San Francisco and convert to Celsius',
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+ 'stream': False
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+ })
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+
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+ print(response.json()['response'])
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+ ```
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+
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+ for Instruct models:
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+ ```bash
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+ curl http://localhost:11434/api/chat -d '{
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+ "model": "llama3.2",
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+ "stream": false,
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+ "messages": [
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+ {"role": "system", "content": "You are a helpful assistant."},
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+ {"role": "user", "content": "Why is the sky blue?"}
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+ ]
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+ }'
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+ ```
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+
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+ ```python
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+ from ollama import chat
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+
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+ # Your custom model name here
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+ model_name = "qwen-7b:toolcall"
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+
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+ messages = [
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+ {"role": "system", "content": "You are an instruct model."},
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+ {"role": "user", "content": "Explain how to use this custom model in Python."}
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+ ]
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+
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+ response = chat(model=model_name, messages=messages)
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+ print(response.message.content)
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+ ```
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+
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+
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+ ***ReSearch***, a novel framework that trains LLMs to ***Re***ason with ***Search*** via reinforcement learning without using any supervised data on reasoning steps. Our approach treats search operations as integral components of the reasoning chain, where when and how to perform searches is guided by text-based thinking, and search results subsequently influence further reasoning.
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+
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+
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+
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+
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+ ## Usage
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+
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+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
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+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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+ more details, including on how to concatenate multi-part files.
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+
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+
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+
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+ ## Provided Quants
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+
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+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q2_K.gguf) | Q2_K | 3.1 | |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.IQ4_XS.gguf) | IQ4_XS | 4.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
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+ | [GGUF](https://huggingface.co/mradermacher/ReSearch-Qwen-7B-GGUF/resolve/main/ReSearch-Qwen-7B.f16.gguf) | f16 | 15.3 | 16 bpw, overkill |
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+
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+ Here is a handy graph by ikawrakow comparing some lower-quality quant
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+ types (lower is better):
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+
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+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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+ ollama run qwen-7b:toolcall
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+ "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
199
+ "clean_up_tokenization_spaces": false,
200
+ "eos_token": "<|endoftext|>",
201
+ "errors": "replace",
202
+ "model_max_length": 131072,
203
+ "pad_token": "<|endoftext|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
vocab.json ADDED
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