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+

README.md

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+---
+base_model:
+- tiiuae/Falcon-H1R-7B
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+license: other
+license_name: falcon-llm-license
+license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html
+tags:
+- falcon-h1r
+---
+
+<img src="https://huggingface.co/datasets/tiiuae/reasoning-images/resolve/main/falcon-h1r-logo.png" alt="drawing" width="800"/>
+
+# Falcon-H1R-7B-FP8
+
+This repository presents post FP8 quantized **Falcon-H1R-7B-FP8** via NVIDIA Model Optimizer, enabling efficient inference while preserving the strong reasoning introduced in the paper [Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scaling](https://huggingface.co/papers/2601.02346). 
+
+[Falcon-H1R-7B](https://huggingface.co/tiiuae/Falcon-H1R-7B) was trained via cold-start supervised fine-tuning with long reasoning traces and further enhanced by scaling RL with GRPO. The model demonstrates outstanding performance across various benchmark evaluations, including mathematics, programming, instruction following, and general logic.
+
+## Model Description
+
+- **Developed by:** [Technology Innovation Institute](https://www.tii.ae)
+- **Model type:** Causal decoder-only
+- **Architecture:** Hybrid (Transformers + Mamba2) architecture
+- **Language(s):** English, Multilingual
+- **License:** [Falcon-LLM License](https://falconllm.tii.ae/falcon-terms-and-conditions.html)
+
+## Details
+
+For more details on FP8 post-quantization for this model, please refer to the [Falcon-H1R-FP8 technical blogpost](https://falcon-lm.github.io/blog/falcon-h1r-7b-fp8).
+
+For more details about the training protocol of this model, please refer to the [Falcon-H1R technical blogpost](https://falcon-lm.github.io/blog/falcon-h1r-7b) and [Technical Report](https://github.com/tiiuae/falcon-h1r/blob/main/tech_report.pdf).
+
+# Usage
+
+Currently to use this model, you can either rely on Hugging Face `transformers`, `vLLM` or `SGLang` library.
+
+## Inference
+
+Make sure to install the latest version of `transformers` or `vLLM` or `SGLang`.
+
+```bash
+pip install transformers
+pip install mamba-ssm[causal-conv1d]
+```
+
+For vLLM, make sure to install latest `vllm`:
+
+```bash
+pip install vllm --extra-index-url https://wheels.vllm.ai/nightly
+```
+
+- **FP8 support (vLLM)**: FP8 enablement from vLLM PR #32728 has been merged: [PR](https://github.com/vllm-project/vllm/pull/32728).
+- **Memory footprint**: Model weight memory drops from 14.2 GB (BF16) to 7.9 GB (FP8).
+- **Throughput**: Inference throughput improves from ~1.2× to up to 1.5×, depending on batch size, prompt length, and generation length, with minimal accuracy impact for this post-training FP8-quantized model.
+- **Tensor parallelism (quantized models)**: Tensor parallel enablement from vLLM PR #33257 has been merged: [PR](https://github.com/vllm-project/vllm/pull/33257).
+
+## Sampling Parameters
+
+We recommend using a **temperature** of **0.6** and **top-p** as **0.95** with max new tokens up to 65536.
+For supported frameworks, you can adjust the repetition_penalty and presence_penalty parameters to reduce endless repetitions.
+
+## vLLM
+
+For vLLM, simply start a server by executing the command below:
+
+<details>
+<summary> Click to expand </summary>
+<br>
+  
+```python
+vllm serve tiiuae/Falcon-H1R-7B-FP8 \
+  --tensor-parallel-size 1 \
+  --data-parallel-size 1 \
+  --reasoning-parser deepseek_r1
+  --quantization modelopt
+```  
+<br>
+Additional flags:
+
+* You can reduce `--max-model-len` to preserve memory. Default value is `262144` which is quite large but not necessary for most scenarios.
+* For function calling, append `--enable-auto-tool-choice` and `--tool-call-parser hermes` to the vllm serve command.
+
+
+vLLM client execution code:
+```python
+from openai import OpenAI
+import json
+
+client = OpenAI(
+    base_url="http://localhost:8000/v1",
+    api_key="EMPTY",
+)
+
+completion = client.chat.completions.create(
+    model="tiiuae/Falcon-H1R-7B-FP8",
+    messages=[
+        {"role": "user", "content": "If the product of two numbers is 360 and their GCD is 6, what is their LCM?"},
+    ],
+    temperature=0.6,
+    top_p=0.95,
+    max_tokens=65536
+)
+
+msg = completion.choices[0].message
+
+print(json.dumps({
+    "reasoning": msg.reasoning_content,
+    "answer": msg.content
+}, indent=2))
+```
+</details>
+<br>
+
+# Evaluation
+
+Falcon-H1R achieves state of art results in reasoning benchmarks. Please refer to the [Falcon-H1R-7B](https://huggingface.co/tiiuae/Falcon-H1R-7B) BF16 model card for full benchmark details.
+The table below highlights accuracy comparisons on selected benchmarks between the Falcon-H1R BF16 checkpoint and the Falcon-H1R FP8 post-quantized checkpoint.
+
+<table border="1" style="width: 100%; text-align: center; border-collapse: collapse;">
+    <colgroup>
+        <col style="width: 6%;">
+        <col style="width: 6%;">
+        <col style="width: 6%;">
+    </colgroup>
+    <thead>
+        <tr>
+            <th>Benchmark</th>
+            <th>Falcon-H1R-7B BF16</th>  
+            <th>Falcon-H1R-7B FP8</th>            
+        </tr>
+    </thead>
+    <tbody>
+        <tr>
+            <td>AIME25</td>
+            <td>83.1</td>
+            <td>82.3</td>            
+        </tr>
+        <tr>
+            <td>LCBv5-v6</td>
+            <td>68.6</td>
+            <td>67.6</td>
+        </tr>
+        <tr>
+            <td>GPQA-D</td>
+            <td>61.3</td>
+            <td>61.2</td>
+        </tr>
+    </tbody>
+</table>
+
+# Useful links
+
+- View [our FP8 release blogpost](https://falcon-lm.github.io/blog/falcon-h1r-7b-fp8).
+- View [our release blogpost](https://falcon-lm.github.io/blog/falcon-h1r-7b).
+- View [our technical report](https://huggingface.co/papers/2601.02346).
+- Feel free to join [our discord server](https://discord.gg/Cbek57PrZE) if you have any questions or to interact with our researchers and developers.
+
+# Acknowledgements
+We sincerely thank the NVIDIA team — Sergio Perez, Shengliang Xu, Vadim Gimpelson, Mireille Fares, Liana Mikaelyan, Amit Kushwaha, and Adam Czekalowski — for their valuable collaboration and support in post-quantizing [Falcon-H1R-7B](https://huggingface.co/tiiuae/Falcon-H1R-7B) to FP8.
+
+# Citation
+
+If the Falcon-H1R family of reasoning models is helpful to your work, feel free to give us a cite.
+
+```
+@misc{falcon-h1r,
+      title={Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scaling}, 
+      author={Falcon LLM Team and Iheb Chaabane and Puneesh Khanna and Suhail Mohmad and Slim Frikha and Shi Hu and Abdalgader Abubaker and Reda Alami and Mikhail Lubinets and Mohamed El Amine Seddik and Hakim Hacid},
+      year={2026},
+      eprint={2601.02346},
+      archivePrefix={arXiv},
+      primaryClass={cs.AI},
+      url={https://arxiv.org/abs/2601.02346}, 
+}
+```

chat_template.jinja

@@ -0,0 +1,101 @@
+{# --- System Prompt Handling --- #}
+{%- if messages and messages[0]['role'] == 'system' %}
+  {% set system_msg = messages[0]['content'] %}  
+  {%- set remaining_messages = messages[1:] %}
+{%- else %}
+  {% set system_msg = "You are Falcon, a helpful AI assistant created by Technology Innovation Institute (TII). To answer the user's question, you first think about the reasoning process and then provide the user with the answer. The reasoning process is enclosed within <think> </think> tags, i.e., <think> reasoning process here </think> answer here." %}
+  {%- set remaining_messages = messages %}
+{%- endif %}
+
+{%- if tools %}
+<|im_start|>system
+{{ system_msg }}
+# Tools
+You may call one or more functions to assist with the user query. You are provided with function signatures within <tools></tools> XML tags.
+<tools>
+{%- for tool in tools %}
+{{- "" }}
+{{ tool | tojson }}
+{%- endfor %}
+{{- "" }}
+</tools>
+For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
+<tool_call>
+{"name": <function-name>, "arguments": <args-json-object>}
+</tool_call>
+<|im_end|>
+
+{%- else %}
+<|im_start|>system
+{{ system_msg }}
+<|im_end|>
+{%- endif %}
+
+{# --- Render remaining messages --- #}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}{%- for message in remaining_messages %}
+  {%- set content = message.get('content','') %}
+  {%- if message['role'] == 'user' %}
+    {{- '<|im_start|>' + message['role'] + '\n' + content + '<|im_end|>\n' }}
+  {%- elif message['role'] == 'assistant' %}
+    {{- '<|im_start|>' + message.role + '\n' }}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- content + '\n' }}
+            {%- endif %}
+        {%- else %}
+            {{- content + '\n' }}
+        {%- endif %}
+    {%- if tools and message.tool_calls %}
+      {%- for tool_call in message.tool_calls %}
+          {%- if tool_call.function is defined %}
+              {%- set tool_call = tool_call.function %}
+          {%- endif %}
+          {{-'<tool_call>\n' }}
+          {{- '{"name": "'+ tool_call.name + '", "arguments":' }}
+          {%- if tool_call.arguments is string -%}
+          {{ tool_call.arguments }}
+          {%- else -%}
+          {{ tool_call.arguments | tojson }}
+          {%- endif -%}
+          {{- '}' }}
+          {{- '\n</tool_call>\n' }}
+      {%- endfor %}
+    {%- endif %}
+    {%- if not loop.last %}
+      {{- '<|im_end|>' + '\n' }}
+    {%- else %}
+      {{- '<|im_end|>' }}
+    {%- endif %}
+  {%- elif message['role'] == 'tool' %}
+    {# Tool responses treated as user messages #}
+    {%- 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 %}
+  {# --- Add generation prompt after last message if requested --- #}
+  {%- if loop.last and add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+  {%- endif %}
+{%- endfor %}

config.json

@@ -0,0 +1,97 @@
+{
+    "architectures": [
+        "FalconH1ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attention_in_multiplier": 1.0,
+    "attention_out_multiplier": 0.10416666666666669,
+    "attn_layer_indices": null,
+    "bos_token_id": 1,
+    "dtype": "bfloat16",
+    "embedding_multiplier": 5.656854249492381,
+    "eos_token_id": 11,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 3072,
+    "initializer_range": 0.02,
+    "intermediate_size": 12288,
+    "key_multiplier": 0.030690398488999456,
+    "lm_head_multiplier": 0.013020833333333334,
+    "mamba_chunk_size": 128,
+    "mamba_conv_bias": true,
+    "mamba_d_conv": 4,
+    "mamba_d_head": 128,
+    "mamba_d_ssm": 3072,
+    "mamba_d_state": 256,
+    "mamba_expand": 2,
+    "mamba_n_groups": 1,
+    "mamba_n_heads": 24,
+    "mamba_norm_before_gate": false,
+    "mamba_proj_bias": false,
+    "mamba_rms_norm": true,
+    "mamba_use_mlp": true,
+    "max_position_embeddings": 262144,
+    "mlp_bias": false,
+    "mlp_expansion_factor": 8,
+    "mlp_multipliers": [
+        0.2946278254943948,
+        0.032552083333333336
+    ],
+    "model_type": "falcon_h1",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 44,
+    "num_key_value_heads": 2,
+    "num_logits_to_keep": 1,
+    "pad_token_id": 0,
+    "projectors_bias": false,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 100000000000,
+    "ssm_in_multiplier": 0.4166666666666667,
+    "ssm_multipliers": [
+        0.3535533905932738,
+        0.25,
+        0.1767766952966369,
+        0.5,
+        0.3535533905932738
+    ],
+    "ssm_out_multiplier": 0.11785113019775792,
+    "tie_word_embeddings": false,
+    "transformers_version": "4.57.0",
+    "use_cache": true,
+    "vocab_size": 130048,
+    "quantization_config": {
+        "config_groups": {
+            "group_0": {
+                "input_activations": {
+                    "dynamic": false,
+                    "num_bits": 8,
+                    "type": "float"
+                },
+                "weights": {
+                    "dynamic": false,
+                    "num_bits": 8,
+                    "type": "float"
+                },
+                "targets": [
+                    "Linear"
+                ]
+            }
+        },
+        "ignore": [
+            "lm_head"
+        ],
+        "quant_algo": "FP8",
+        "kv_cache_scheme": {
+            "dynamic": false,
+            "num_bits": 8,
+            "type": "float"
+        },
+        "producer": {
+            "name": "modelopt",
+            "version": "0.41.0rc2.dev48+g5cc2a5451"
+        },
+        "quant_method": "modelopt"
+    }
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": [11, 228],
+  "pad_token_id": 0,
+  "transformers_version": "4.52.0.dev0"
+}

hf_quant_config.json

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+{
+    "producer": {
+        "name": "modelopt",
+        "version": "0.41.0rc2.dev48+g5cc2a5451"
+    },
+    "quantization": {
+        "quant_algo": "FP8",
+        "kv_cache_quant_algo": "FP8",
+        "exclude_modules": [
+            "lm_head"
+        ]
+    }
+}

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+    ">>UNUSED_991<<",
+    ">>UNUSED_992<<",
+    ">>UNUSED_993<<",
+    ">>UNUSED_994<<",
+    ">>UNUSED_995<<",
+    ">>UNUSED_996<<",
+    ">>UNUSED_997<<",
+    ">>UNUSED_998<<",
+    ">>UNUSED_999<<",
+    ">>UNUSED_1000<<",
+    ">>UNUSED_1001<<",
+    ">>UNUSED_1002<<",
+    ">>UNUSED_1003<<",
+    ">>UNUSED_1004<<",
+    ">>UNUSED_1005<<",
+    ">>UNUSED_1006<<",
+    ">>UNUSED_1007<<",
+    ">>UNUSED_1008<<",
+    ">>UNUSED_1009<<",
+    ">>UNUSED_1010<<",
+    ">>UNUSED_1011<<",
+    ">>UNUSED_1012<<",
+    ">>UNUSED_1013<<",
+    ">>UNUSED_1014<<",
+    ">>UNUSED_1015<<",
+    ">>UNUSED_1016<<",
+    ">>UNUSED_1017<<",
+    ">>UNUSED_1018<<",
+    ">>UNUSED_1019<<",
+    ">>UNUSED_1020<<",
+    ">>UNUSED_1021<<",
+    ">>UNUSED_1022<<",
+    ">>UNUSED_1023<<"
+  ],
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|end_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|end_of_text|>"
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a1a906251e685c2ff1fbb0ab2e36d9d1b276e6283a7a9a3e721c5b1923c017c0
+size 10534300