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Model: KiwiMate/KiwiMate-Mini-Preview Source: Original Platform
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KiwiMate-Mini-Preview-MODEL_CARD.md
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KiwiMate-Mini-Preview-MODEL_CARD.md
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---
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language: en
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license: apache-2.0
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base_model: meta-llama/Llama-3.2-3B-Instruct
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tags:
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- unsloth
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- text-generation-inference
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- conversational
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- gguf
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- llama
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datasets:
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- KiwiMate/KiwiMate-Mini-training
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pipeline_tag: text-generation
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---
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# KiwiMate-Mini-Preview
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**KiwiMate-Mini-Preview** is a lightweight, New Zealand–flavoured conversational language model, fine-tuned for the [KiwiMate](https://kiwimate.net) AI companion app. It is the smallest model in the KiwiMate model family and is designed for fast, low-cost inference on the app's free and lower-tier subscription plans.
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> ⚠️ **Preview status:** This is a prototype release. The name reflects its preview status — expect breaking changes, retraining, and behavioural shifts before a stable v1 release.
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## Model Details
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| | |
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|---|---|
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| **Developed by** | KiwiMate / KyleCodeKiwi |
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| **Base model** | Llama 3.2 3B Instruct |
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| **Architecture** | Llama |
|
||||
| **Parameters** | ~3.21B |
|
||||
| **Fine-tuning framework** | [Unsloth](https://github.com/unslothai/unsloth) |
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| **License** | Apache 2.0 |
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| **Languages** | English (with New Zealand English and Te Reo Māori vocabulary coverage) |
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| **Model class** | `AutoModelForCausalLM` |
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## Intended Use
|
||||
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||||
KiwiMate-Mini-Preview is intended as the default conversational backend for the KiwiMate app, providing:
|
||||
|
||||
- General-purpose chat and assistant-style conversation
|
||||
- New Zealand cultural and "Kiwi" context awareness (slang, geography, fun facts)
|
||||
- Light Te Reo Māori vocabulary recognition and use
|
||||
- Lore and knowledge specific to the KiwiMate app itself ("KiwiMate Origin" data)
|
||||
- Lightweight knowledge support for in-app mini-games
|
||||
|
||||
It is **not** intended for high-stakes, medical, legal, or financial advice, and should not be relied on as an authoritative source on Māori language or tikanga — for genuinely sensitive Te Reo or cultural content, defer to community-governed resources.
|
||||
|
||||
## Training Data
|
||||
|
||||
Fine-tuned on the [`KiwiMate/KiwiMate-Mini-training`](https://huggingface.co/datasets/KiwiMate/KiwiMate-Mini-training) dataset, organised into categories including:
|
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|
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- NZ English
|
||||
- Te Reo Māori
|
||||
- KiwiMate Origin (app-specific lore/identity)
|
||||
- NZ Fun Facts
|
||||
- MiniGame Knowledge
|
||||
|
||||
## Files & Quantizations
|
||||
|
||||
Distributed as `safetensors` (full precision) and GGUF quantizations for efficient local/edge inference:
|
||||
|
||||
| Format | Use case |
|
||||
|---|---|
|
||||
| F16 | Highest fidelity, largest size |
|
||||
| Q6_K | Near-lossless, smaller footprint |
|
||||
| Q4_K_M | Balanced quality/size — recommended default for on-device use |
|
||||
| Q2_K_L | Smallest footprint, lowest fidelity |
|
||||
|
||||
## Deployment
|
||||
|
||||
Served in production via a Hugging Face Inference Endpoint on a T4 GPU with scale-to-zero, fronted by a Supabase Edge Function (OpenAI-compatible proxy) that routes KiwiMate app traffic to this and other KiwiMate model endpoints behind a single API.
|
||||
|
||||
### Known Limitations
|
||||
|
||||
- A server-side mitigation is in place for an occasional role-bleed / over-generation issue (the model sometimes continuing past `<|eot_id|>`), handled via stop-sequence aliases and trimming at the proxy layer.
|
||||
- The long-term fix — adding `<|eot_id|>` (token ID 128009) properly to the training loss and `generation_config.json` — is planned for a future retraining pass rather than this preview.
|
||||
- As a 3B-parameter model, reasoning depth and factual reliability are limited compared to larger models; it is tuned for speed and personality over raw capability.
|
||||
|
||||
## License
|
||||
|
||||
Released under the Apache 2.0 license, consistent with the open weights commitment for the KiwiMate model family.
|
||||
80
README.md
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README.md
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---
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language: en
|
||||
license: apache-2.0
|
||||
base_model: meta-llama/Llama-3.2-3B-Instruct
|
||||
tags:
|
||||
- unsloth
|
||||
- text-generation-inference
|
||||
- conversational
|
||||
- gguf
|
||||
- llama
|
||||
datasets:
|
||||
- KiwiMate/KiwiMate-Mini-training
|
||||
pipeline_tag: text-generation
|
||||
---
|
||||
|
||||
# KiwiMate-Mini-Preview
|
||||
|
||||
**KiwiMate-Mini-Preview** is a lightweight, New Zealand–flavoured conversational language model, fine-tuned for the [KiwiMate](https://kiwimate.net) AI companion app. It is the smallest model in the KiwiMate model family and is designed for fast, low-cost inference on the app's free and lower-tier subscription plans.
|
||||
|
||||
> ⚠️ **Preview status:** This is a prototype release. The name reflects its preview status — expect breaking changes, retraining, and behavioural shifts before a stable v1 release.
|
||||
|
||||
## Model Details
|
||||
|
||||
| | |
|
||||
|---|---|
|
||||
| **Developed by** | KiwiMate / KyleCodeKiwi |
|
||||
| **Base model** | Llama 3.2 3B Instruct |
|
||||
| **Architecture** | Llama |
|
||||
| **Parameters** | ~3.21B |
|
||||
| **Fine-tuning framework** | [Unsloth](https://github.com/unslothai/unsloth) |
|
||||
| **License** | Apache 2.0 |
|
||||
| **Languages** | English (with New Zealand English and Te Reo Māori vocabulary coverage) |
|
||||
| **Model class** | `AutoModelForCausalLM` |
|
||||
|
||||
## Intended Use
|
||||
|
||||
KiwiMate-Mini-Preview is intended as the default conversational backend for the KiwiMate app, providing:
|
||||
|
||||
- General-purpose chat and assistant-style conversation
|
||||
- New Zealand cultural and "Kiwi" context awareness (slang, geography, fun facts)
|
||||
- Light Te Reo Māori vocabulary recognition and use
|
||||
- Lore and knowledge specific to the KiwiMate app itself ("KiwiMate Origin" data)
|
||||
- Lightweight knowledge support for in-app mini-games
|
||||
|
||||
It is **not** intended for high-stakes, medical, legal, or financial advice, and should not be relied on as an authoritative source on Māori language or tikanga — for genuinely sensitive Te Reo or cultural content, defer to community-governed resources.
|
||||
|
||||
## Training Data
|
||||
|
||||
Fine-tuned on the [`KiwiMate/KiwiMate-Mini-training`](https://huggingface.co/datasets/KiwiMate/KiwiMate-Mini-training) dataset, organised into categories including:
|
||||
|
||||
- NZ English
|
||||
- Te Reo Māori
|
||||
- KiwiMate Origin (app-specific lore/identity)
|
||||
- NZ Fun Facts
|
||||
- MiniGame Knowledge
|
||||
|
||||
## Files & Quantizations
|
||||
|
||||
Distributed as `safetensors` (full precision) and GGUF quantizations for efficient local/edge inference:
|
||||
|
||||
| Format | Use case |
|
||||
|---|---|
|
||||
| F16 | Highest fidelity, largest size |
|
||||
| Q6_K | Near-lossless, smaller footprint |
|
||||
| Q4_K_M | Balanced quality/size — recommended default for on-device use |
|
||||
| Q2_K_L | Smallest footprint, lowest fidelity |
|
||||
|
||||
## Deployment
|
||||
|
||||
Served in production via a Hugging Face Inference Endpoint on a T4 GPU with scale-to-zero, fronted by a Supabase Edge Function (OpenAI-compatible proxy) that routes KiwiMate app traffic to this and other KiwiMate model endpoints behind a single API.
|
||||
|
||||
### Known Limitations
|
||||
|
||||
- A server-side mitigation is in place for an occasional role-bleed / over-generation issue (the model sometimes continuing past `<|eot_id|>`), handled via stop-sequence aliases and trimming at the proxy layer.
|
||||
- The long-term fix — adding `<|eot_id|>` (token ID 128009) properly to the training loss and `generation_config.json` — is planned for a future retraining pass rather than this preview.
|
||||
- As a 3B-parameter model, reasoning depth and factual reliability are limited compared to larger models; it is tuned for speed and personality over raw capability.
|
||||
|
||||
## License
|
||||
|
||||
Released under the Apache 2.0 license, consistent with the open weights commitment for the KiwiMate model family.
|
||||
93
chat_template.jinja
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93
chat_template.jinja
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{{- bos_token }}
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{%- if custom_tools is defined %}
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{%- set tools = custom_tools %}
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{%- endif %}
|
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{%- if not tools_in_user_message is defined %}
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||||
{%- set tools_in_user_message = true %}
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||||
{%- endif %}
|
||||
{%- if not date_string is defined %}
|
||||
{%- if strftime_now is defined %}
|
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{%- set date_string = strftime_now("%d %b %Y") %}
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{%- else %}
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{%- set date_string = "26 Jul 2024" %}
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{%- endif %}
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||||
{%- endif %}
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||||
{%- if not tools is defined %}
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{%- set tools = none %}
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{%- endif %}
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||||
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{#- This block extracts the system message, so we can slot it into the right place. #}
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{%- set system_message = "" %}
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{%- endif %}
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{#- System message #}
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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{%- if tools is not none %}
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{{- "Environment: ipython\n" }}
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{%- endif %}
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{{- "Cutting Knowledge Date: December 2023\n" }}
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{{- "Today Date: " + date_string + "\n\n" }}
|
||||
{%- if tools is not none and not tools_in_user_message %}
|
||||
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
|
||||
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
|
||||
{{- "Do not use variables.\n\n" }}
|
||||
{%- for t in tools %}
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{{- t | tojson(indent=4) }}
|
||||
{{- "\n\n" }}
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{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- system_message }}
|
||||
{{- "<|eot_id|>" }}
|
||||
|
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{#- Custom tools are passed in a user message with some extra guidance #}
|
||||
{%- if tools_in_user_message and not tools is none %}
|
||||
{#- Extract the first user message so we can plug it in here #}
|
||||
{%- if messages | length != 0 %}
|
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{%- set first_user_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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||||
{%- else %}
|
||||
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
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||||
{%- endif %}
|
||||
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
|
||||
{{- "Given the following functions, please respond with a JSON for a function call " }}
|
||||
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
|
||||
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
|
||||
{{- "Do not use variables.\n\n" }}
|
||||
{%- for t in tools %}
|
||||
{{- t | tojson(indent=4) }}
|
||||
{{- "\n\n" }}
|
||||
{%- endfor %}
|
||||
{{- first_user_message + "<|eot_id|>"}}
|
||||
{%- endif %}
|
||||
|
||||
{%- for message in messages %}
|
||||
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
|
||||
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
|
||||
{%- elif 'tool_calls' in message %}
|
||||
{%- if not message.tool_calls|length == 1 %}
|
||||
{{- raise_exception("This model only supports single tool-calls at once!") }}
|
||||
{%- endif %}
|
||||
{%- set tool_call = message.tool_calls[0].function %}
|
||||
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
|
||||
{{- '{"name": "' + tool_call.name + '", ' }}
|
||||
{{- '"parameters": ' }}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{{- "}" }}
|
||||
{{- "<|eot_id|>" }}
|
||||
{%- elif message.role == "tool" or message.role == "ipython" %}
|
||||
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
|
||||
{%- if message.content is mapping or message.content is iterable %}
|
||||
{{- message.content | tojson }}
|
||||
{%- else %}
|
||||
{{- message.content }}
|
||||
{%- endif %}
|
||||
{{- "<|eot_id|>" }}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
|
||||
{%- endif %}
|
||||
37
config.json
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37
config.json
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|
||||
{
|
||||
"architectures": [
|
||||
"LlamaForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 128000,
|
||||
"torch_dtype": "bfloat16",
|
||||
"eos_token_id": 128009,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 3072,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 8192,
|
||||
"max_position_embeddings": 131072,
|
||||
"mlp_bias": false,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 24,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": 128004,
|
||||
"pretraining_tp": 1,
|
||||
"rms_norm_eps": 1e-05,
|
||||
"rope_scaling": {
|
||||
"factor": 32.0,
|
||||
"high_freq_factor": 4.0,
|
||||
"low_freq_factor": 1.0,
|
||||
"original_max_position_embeddings": 8192,
|
||||
"rope_type": "llama3"
|
||||
},
|
||||
"rope_theta": 500000.0,
|
||||
"tie_word_embeddings": true,
|
||||
"unsloth_fixed": true,
|
||||
"unsloth_version": "2026.5.2",
|
||||
"use_cache": true,
|
||||
"vocab_size": 128256
|
||||
}
|
||||
7
generation_config.json
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generation_config.json
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|
||||
{
|
||||
"bos_token_id": 1,
|
||||
"eos_token_id": 2,
|
||||
"max_length": 262144,
|
||||
"pad_token_id": 11,
|
||||
"transformers_version": "5.0.0.dev0"
|
||||
}
|
||||
3
model-00001-of-00002.safetensors
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3
model-00001-of-00002.safetensors
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
|
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size 4965799096
|
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model-00002-of-00002.safetensors
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model-00002-of-00002.safetensors
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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|
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size 1459729952
|
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261
model.safetensors.index.json
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261
model.safetensors.index.json
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@@ -0,0 +1,261 @@
|
||||
{
|
||||
"metadata": {
|
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|
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||||
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||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2067
tokenizer_config.json
Normal file
2067
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
3
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Normal file
3
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Normal file
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Normal file
3
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Normal file
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3
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Normal file
@@ -0,0 +1,3 @@
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3
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Normal file
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||||
Reference in New Issue
Block a user