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Model: eulogik/Bharat-Tiny-LLM-fused
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---
license: apache-2.0
language:
- hi
- en
- hne
tags:
- hinglish
- hindi
- indian-languages
- fused
- pytorch
- fp16
- qwen
- qwen2
- bharat
- indic-nlp
base_model: Qwen/Qwen2.5-1.5B
library_name: transformers
pipeline_tag: text-generation
---
# Bharat-Tiny-LLM (fused · fp16)
This is the **full-precision fused model** for [Bharat-Tiny-LLM](https://huggingface.co/eulogik/Bharat-Tiny-LLM) —
the LoRA adapter merged into the base [Qwen2.5-1.5B](https://huggingface.co/Qwen/Qwen2.5-1.5B) weights,
in PyTorch `float16`.
Use this repo when you want to:
- run inference on CPU / CUDA with `transformers`,
- fine-tune further, or
- produce your own quantized builds (GGUF, MLX, etc.).
> Built by [eulogik](https://eulogik.com)
## For most users
You probably want a smaller, ready-to-run build instead:
| Build | Repo | Size | Use |
|-------|------|------|-----|
| **MLX 4-bit** (edge / Apple Silicon) | [`eulogik/Bharat-Tiny-LLM`](https://huggingface.co/eulogik/Bharat-Tiny-LLM) | ~880 MB | Recommended for Mac / on-device |
| **GGUF Q4_K_M** (llama.cpp, Android / Pi / CPU) | [`eulogik/Bharat-Tiny-LLM-GGUF`](https://huggingface.co/eulogik/Bharat-Tiny-LLM-GGUF) | ~1.06 GB | Cross-platform, llama.cpp |
| **PyTorch fp16** (this repo) | `eulogik/Bharat-Tiny-LLM-fused` | ~3.3 GB | Server / fine-tuning base |
## Quick start (transformers)
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("eulogik/Bharat-Tiny-LLM-fused")
tokenizer = AutoTokenizer.from_pretrained("eulogik/Bharat-Tiny-LLM-fused")
messages = [{"role": "user", "content": "Chai peete hain?"}]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt")
out = model.generate(
**inputs,
max_new_tokens=256,
temperature=0.3,
top_p=0.85,
repetition_penalty=1.25,
no_repeat_ngram_size=3,
do_sample=True,
)
print(tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
```
> ⚠️ **Generation config matters.** The base Qwen2.5-1.5B emits garbled out-of-script tokens
> at high temperature. Always use `temperature ≈ 0.3` + `repetition_penalty ≥ 1.25` +
> `no_repeat_ngram_size = 3`. The [`bharat-tiny-llm`](https://pypi.org/project/bharat-tiny-llm/)
> PyPI package applies these for you.
## Links
- 🤗 Edge model (MLX): https://huggingface.co/eulogik/Bharat-Tiny-LLM
- 🤗 GGUF (llama.cpp): https://huggingface.co/eulogik/Bharat-Tiny-LLM-GGUF
- 🚀 Demo: https://huggingface.co/spaces/eulogik/Bharat-Tiny-LLM
- 💻 Source: https://github.com/eulogik/Bharat-Tiny-LLM
- 📦 PyPI: https://pypi.org/project/bharat-tiny-llm/
- 🏢 Built by [eulogik](https://eulogik.com)
## License
Apache-2.0 (base Qwen2.5-1.5B weights Apache-2.0; LoRA adapter Apache-2.0).

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{%- if tools %}
{{- '<|im_start|>system\n' }}
{%- if messages[0]['role'] == 'system' %}
{{- messages[0]['content'] }}
{%- else %}
{{- 'You are a helpful assistant.' }}
{%- endif %}
{{- "\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>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\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" }}
{%- else %}
{%- if messages[0]['role'] == 'system' %}
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
{%- else %}
{{- '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- for message in messages %}
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>' + message.role }}
{%- if message.content %}
{{- '\n' + message.content }}
{%- endif %}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '\n<tool_call>\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{{- tool_call.arguments | tojson }}
{{- '}\n</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{{- message.content }}
{{- '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}

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{
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"dtype": "float16",
"eos_token_id": 151643,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 8960,
"layer_types": [
"full_attention",
"full_attention",
"full_attention",
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"full_attention",
"full_attention",
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],
"max_position_embeddings": 131072,
"max_window_layers": 28,
"model_type": "qwen2",
"num_attention_heads": 12,
"num_hidden_layers": 28,
"num_key_value_heads": 2,
"pad_token_id": null,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 1000000.0,
"rope_type": "default"
},
"sliding_window": null,
"tie_word_embeddings": true,
"transformers_version": "5.12.1",
"use_cache": true,
"use_mrope": false,
"use_sliding_window": false,
"vocab_size": 151936
}

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{
"bos_token_id": 151643,
"eos_token_id": 151643,
"pad_token_id": 151643
}

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{
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": null,
"clean_up_tokenization_spaces": false,
"eos_token": "<|endoftext|>",
"errors": "replace",
"extra_special_tokens": [
"<|im_start|>",
"<|im_end|>",
"<|object_ref_start|>",
"<|object_ref_end|>",
"<|box_start|>",
"<|box_end|>",
"<|quad_start|>",
"<|quad_end|>",
"<|vision_start|>",
"<|vision_end|>",
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],
"is_local": false,
"local_files_only": false,
"model_max_length": 131072,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null
}