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Model: TeichAI/Qwen3-8B-Gemini-2.5-Flash-Distill-GGUF Source: Original Platform
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**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text
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Qwen3-8B-Gemini-2.5-Flash-Distill-q3_k_s.gguf filter=lfs diff=lfs merge=lfs -text
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Qwen3-8B-Gemini-2.5-Flash-Distill-q3_k_m.gguf filter=lfs diff=lfs merge=lfs -text
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Qwen3-8B-Gemini-2.5-Flash-Distill-q4_k_m.gguf filter=lfs diff=lfs merge=lfs -text
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Qwen3-8B-Gemini-2.5-Flash-Distill-q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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qwen3-8b.F16.gguf filter=lfs diff=lfs merge=lfs -text
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59
Modelfile
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Modelfile
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FROM qwen3-8b.Q8_0.gguf
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TEMPLATE """{{- if .Messages }}
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{{- if or .System .Tools }}<|im_start|>system
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{{- if .System }}
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{{ .System }}
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{{- end }}
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{{- if .Tools }}
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# Tools
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You may call one or more functions to assist with the user query.
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You are provided with function signatures within <tools></tools> XML tags:
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<tools>
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{{- range .Tools }}
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{"type": "function", "function": {{ .Function }}}
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{{- end }}
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</tools>
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For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
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<tool_call>
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{"name": <function-name>, "arguments": <args-json-object>}
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</tool_call>
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{{- end }}<|im_end|>
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{{ end }}
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{{- range $i, $_ := .Messages }}
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{{- $last := eq (len (slice $.Messages $i)) 1 -}}
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{{- if eq .Role "user" }}<|im_start|>user
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{{ .Content }}<|im_end|>
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{{ else if eq .Role "assistant" }}<|im_start|>assistant
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{{ if .Content }}{{ .Content }}
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{{- else if .ToolCalls }}<tool_call>
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{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
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{{ end }}</tool_call>
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{{- end }}{{ if not $last }}<|im_end|>
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{{ end }}
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{{- else if eq .Role "tool" }}<|im_start|>user
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<tool_response>
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{{ .Content }}
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</tool_response><|im_end|>
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{{ end }}
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{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant
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{{ end }}
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{{- end }}
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{{- else }}
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{{- if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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{{ end }}{{ if .Prompt }}<|im_start|>user
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{{ .Prompt }}<|im_end|>
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{{ end }}<|im_start|>assistant
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{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}"""
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PARAMETER stop "<|im_end|>"
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PARAMETER stop "<|im_start|>"
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PARAMETER temperature 0.6
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PARAMETER min_p 0.0
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PARAMETER top_k 20
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PARAMETER top_p 0.95
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PARAMETER repeat_penalty 1
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3
Qwen3-8B-Gemini-2.5-Flash-Distill-q3_k_m.gguf
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Qwen3-8B-Gemini-2.5-Flash-Distill-q3_k_m.gguf
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Qwen3-8B-Gemini-2.5-Flash-Distill-q3_k_s.gguf
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Qwen3-8B-Gemini-2.5-Flash-Distill-q3_k_s.gguf
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version https://git-lfs.github.com/spec/v1
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3
Qwen3-8B-Gemini-2.5-Flash-Distill-q4_k_m.gguf
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Qwen3-8B-Gemini-2.5-Flash-Distill-q4_k_m.gguf
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version https://git-lfs.github.com/spec/v1
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3
Qwen3-8B-Gemini-2.5-Flash-Distill-q8_0.gguf
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3
Qwen3-8B-Gemini-2.5-Flash-Distill-q8_0.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:fe7425bb564f3538c673435c57a4a0f6ad5ff37fcfdeaf6a30c27d73a2d1e0ac
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43
README.md
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README.md
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---
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base_model:
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- TeichAI/Qwen3-8B-Gemini-2.5-Flash-Distill
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen3
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license: apache-2.0
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language:
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- en
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datasets:
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- TeichAI/gemini-2.5-flash-11000x
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---
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# Qwen3 8B x Gemini 2.5 Flash Distill
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This model was trained on a large **Gemini 2.5 Flash** dataset.
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- 🤖 Related Models:
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| Model | Effective parameters | Active parameters |
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| ------------- | ------------- | ------------- |
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| [`TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF`](https://huggingface.co/TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF) | 30 B | 3 B |
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| [`TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF`](https://huggingface.co/TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF) | 4 B | 4 B |
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- 🧬 Datasets:
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- `TeichAI/gemini-2.5-flash-11000x`
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- 🏗 Base Model:
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- `unsloth/Qwen3-8B`
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- ⚡ Use cases:
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- Coding
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- Science
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- Legal
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- History
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- Marketing
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- General Purpose
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- ∑ Stats (Dataset)
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- Costs: $ 134 (USD)
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- Total tokens (input + output): 54.4 M
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config.json
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"torch_dtype": "bfloat16",
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 12288,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 40960,
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"max_window_layers": 36,
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"model_type": "qwen3",
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"num_attention_heads": 32,
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"num_hidden_layers": 36,
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"num_key_value_heads": 8,
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"pad_token_id": 151654,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"rope_theta": 1000000,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"transformers_version": "4.56.2",
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"unsloth_fixed": true,
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"unsloth_version": "2025.11.3",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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1
configuration.json
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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3
qwen3-8b.F16.gguf
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qwen3-8b.F16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:57f447ac97203f75a4fbb8f1fd24119eaee8bcf106eb5989c2a803afa99551b8
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size 16388043552
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