4-bit Autotrain compatible Awq Conversational Endpoints compatible Mistral Quantized Region:us Safetensors Sharded Tensorflow
Model Card on HF 🤗: https://huggingface.co/dan-kwiat/codestral-learn-60-epoch-4-f-awq
Codestral Learn 60 Epoch 4 F AWQ Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
Codestral Learn 60 Epoch 4 F AWQ Parameters and Internals
| LLM Name | Codestral Learn 60 Epoch 4 F AWQ |
| Repository 🤗 | https://huggingface.co/dan-kwiat/codestral-learn-60-epoch-4-f-awq |
| Model Size | 3.3b |
| Required VRAM | 12.2 GB |
| Updated | 2025-09-28 |
| Maintainer | dan-kwiat |
| Model Type | mistral |
| Model Files | |
| AWQ Quantization | Yes |
| Quantization Type | awq |
| Model Architecture | MistralForCausalLM |
| License | MNPL-0.1 |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.41.2 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <unk> |
| Vocabulary Size | 32768 |
| Torch Data Type | float16 |
Rank the Codestral Learn 60 Epoch 4 F AWQ Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124