初始化项目，由ModelHub XC社区提供模型
Model: karwalski/toke Source: Original Platform
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109
README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- toke
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- code-generation
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- programming-language
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- qwen2
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- qlora
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- fine-tuned
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- awq
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- 4bit
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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pipeline_tag: text-generation
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model-index:
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- name: toke-7b-gate2
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results:
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- task:
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type: text-generation
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name: Code Generation
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metrics:
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- name: Compilation Pass@1
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type: pass@1
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value: 100
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verified: true
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- name: Functional Pass@1
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type: pass@1
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value: 8
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verified: true
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---
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# toke-7b-gate2
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A 7B parameter language model fine-tuned to generate code in **toke**, a programming language designed to reduce token cost of AI-generated code. This model writes syntactically valid toke **100% of the time**.
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## Model Details
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| Property | Value |
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|---|---|
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| **Base model** | [Qwen 2.5 Coder 7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) |
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| **Method** | QLoRA (rank 64, alpha 128, 3 epochs) |
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| **Training data** | 25,953 records — 18,890 synthetic + 6,069 from [loke](https://github.com/karwalski/loke) production (87K lines) |
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| **Training time** | 37 hours on NVIDIA A10G (24 GB) |
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| **Weights** | AWQ 4-bit quantized (this repo) |
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| **Context length** | 32,768 tokens |
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| **License** | Apache 2.0 |
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## What is toke?
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toke is a statically typed, compiled language with a **55-character alphabet** (lowercase a-z, digits 0-9, and 19 symbols). It compiles to native binaries via LLVM. A purpose-built BPE tokenizer achieves **52% fewer tokens** on average vs cl100k_base.
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- **13 keywords:** `m` `f` `t` `i` `if` `el` `lp` `br` `let` `mut` `as` `rt` `mt`
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- **No comments** in source — documentation lives in companion files (.tkc.md)
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- **Errors as values** — no exceptions, result types with `mt` (match)
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- **Website:** [tokelang.dev](https://tokelang.dev) | **Console:** [console.tokelang.dev](https://console.tokelang.dev)
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## Gate 2 Results (May 2026)
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| Metric | Gate 1 | Gate 2 |
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|---|---|---|
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| Compilation Pass@1 | 63.7% | **100%** |
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| Tasks evaluated | 1,000 | 700 |
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| Functional Pass@1 | — | ~8% |
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| Training records | 73,000 | 25,953 |
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("karwalski/toke", device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained("karwalski/toke")
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prompt = """<|im_start|>system
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Write toke programs. m=mod; f=name(p:type):ret{body}; let x=42; <expr return. Semicolons everywhere. Start with m=.
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<|im_end|>
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<|im_start|>user
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Write a hello world program
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<|im_end|>
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<|im_start|>assistant
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"""
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.2, do_sample=True)
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print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
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# m=hello;i=io:std.io;f=main():i64{io.println("hello world");<0};
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```
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## API Access
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Free API access via [console.tokelang.dev](https://console.tokelang.dev) — no credit card required.
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```bash
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curl -X POST https://api.tokelang.dev/v1/generate \
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-H "X-Api-Key: YOUR_KEY" \
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-H "Content-Type: application/json" \
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-d '{"description": "Return the absolute value of an integer"}'
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```
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## Links
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- [tokelang.dev](https://tokelang.dev) — Project website
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- [console.tokelang.dev](https://console.tokelang.dev) — Free API access
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- [GitHub: toke](https://github.com/karwalski/toke) — Compiler, spec, stdlib
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- [GitHub: loke](https://github.com/karwalski/loke) — 87K lines of production toke
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- [Live tokenizer](https://tokelang.dev/tokenizer) — Compare token counts in-browser
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54
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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69
config.json
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"dtype": "float16",
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 3584,
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"initializer_range": 0.02,
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"intermediate_size": 18944,
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"layer_types": [
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"full_attention",
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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"version": "gemm",
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"zero_point": true
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 1000000.0,
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": false,
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"transformers_version": "5.4.0",
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"use_cache": false,
|
||||
"use_sliding_window": false,
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"vocab_size": 152064
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}
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14
generation_config.json
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generation_config.json
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"repetition_penalty": 1.1,
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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"transformers_version": "5.4.0"
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}
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3
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Normal file
3
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@@ -0,0 +1,3 @@
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29
tokenizer_config.json
Normal file
29
tokenizer_config.json
Normal file
@@ -0,0 +1,29 @@
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}
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Reference in New Issue
Block a user